On the bottom you have access to the archive of SeqAn-related publications. Please see Google Scholar for a complete list of applications that cite SeqAn.

If you use SeqAn in any of your academic works, please cite the latest SeqAn paper:

  • Knut Reinert, Temesgen Hailemariam Dadi, Marcel Ehrhardt, Hannes Hauswedell, Svenja Mehringer, RenĂ© Rahn, Jongkyu Kim, Christopher Pockrandt, Jörg Winkler, Enrico Siragusa, Gianvito Urgese, David Weese, “The SeqAn C++ template library for efficient sequence analysis: A resource for programmers”, vol. 261, 2017-11-10.
    cite this publication
    @article{fu_mi_publications2103,
     abstract = {Background The use of novel algorithmic techniques is pivotal to many important
      problems in life science. For example the sequencing of the human genome (Venter et al., 2001)
      would not have been possible without advanced assembly algorithms and the development of practical
      BWT based read mappers have been instrumental for NGS analysis. However, owing to the high speed
      of technological progress and the urgent need for bioinformatics tools, there was a widening gap
      between state-of-the-art algorithmic techniques and the actual algorithmic components of tools
      that are in widespread use. We previously addressed this by introducing the SeqAn library of
      efficient data types and algorithms in 2008 (D{\"o}ring et al., 2008). Results The SeqAn library
      has matured considerably since its first publication 9 years ago. In this article we review its
      status as an established resource for programmers in the field of sequence analysis and its
      contributions to many analysis tools. Conclusions We anticipate that SeqAn will continue to be a
      valuable resource, especially since it started to actively support various hardware acceleration
      techniques in a systematic manner. Keywords NGS analysis; Software libraries; C++; Data
      structures},
     author = {Knut Reinert and Temesgen Hailemariam Dadi and Marcel Ehrhardt and Hannes Hauswedell and
      Svenja Mehringer and Ren{\'e} Rahn and Jongkyu Kim and Christopher Pockrandt and J{\"o}rg Winkler
      and Enrico Siragusa and Gianvito Urgese and David Weese},
     journal = {Journal of Biotechnology},
     keywords = {NGS analysis; Software libraries; C++; Data structures},
     month = {November},
     pages = {157--168},
     publisher = {ELSEVIER},
     title = {The SeqAn C++ template library for efficient sequence analysis: A resource for
      programmers},
     url = {http://publications.imp.fu-berlin.de/2103/},
     volume = {261},
     year = {2017}
    }

Publications by year

2026

  • Evelin Aasna, Simon G Gottlieb, Marcel Ehrhardt, Knut Reinert, “Dream-stellar: parallel and space efficient exact local alignment”, 2026-02-18.
    cite this publication
    @article{fu_mi_publications3311,
     abstract = {Background: Searching large genomic data sets for local alignments poses a
      computational challenge. A particular obstacle is the handling of repetitive sequences that appear
      in various contexts and incur a high runtime cost. For practical homology search, it is important
      to develop a specific but sensitive filter. Good filters reduce the search space before alignment
      without missing significant matches. Results: We introduce DREAM-Stellar, a parallelized, updated
      version of the pairwise local aligner Stellar. The new aligner, DREAM-Stellar, is composed of four
      steps: preprocessing the queries and references, building a data structure for distributing the
      queries, computing in parallel the results and finally combining them. For distributing the
      queries we use the IBF data structure and a new prefilter for local alignments. We present our
      comparison of five local aligners on simulated and real genomic data and conclude that heuristic
      tools like BLAST miss a large percentage of significant local alignments or "drown" them in
      millions of less significant matches. This new version of Stellar is up to 900 times faster on 32
      parallel threads than its single-threaded predecessor and can find all alignments between a pair
      of genomes in minutes. With that, the runtime of DREAM-Stellar is on par with tools like BLAST
      etc. Conclusions: DREAM-Stellar is very practical and fast on very long sequences which makes it a
      suitable new tool for finding local alignments between genomic sequences under the edit distance
      model. The software is freely available for Linux and Mac OS X at
      https://github.com/seqan/dream-stellar},
     author = {Evelin Aasna and Simon G Gottlieb and Marcel Ehrhardt and Knut Reinert},
     journal = {BMC Bioinformatics},
     month = {February},
     publisher = {Springer Nature},
     title = {Dream-stellar: parallel and space efficient exact local alignment},
     url = {http://publications.imp.fu-berlin.de/3311/},
     year = {2026}
    }

2025

  • Vitor C. Piro, Knut Reinert, “ganon2: up-to-date and scalable metagenomics analysis”, vol. 7, iss. 3, 2025-07-17.
    cite this publication
    @article{fu_mi_publications3142,
     abstract = {The fast growth of public genomic sequence repositories greatly contributes to the
      success of metagenomics. However, they are growing at a faster pace than the computational
      resources to use them. This challenges current methods, which struggle to take full advantage of
      massive and fast data generation. We propose a generational leap in performance and usability with
      ganon2, a sequence classification method that performs taxonomic binning and profiling for
      metagenomics analysis. It indexes large datasets with a small memory footprint, maintaining fast,
      sensitive, and precise classification results. Based on the full NCBI RefSeq and its subsets,
      ganon2 indices are on average 50\% smaller than state-of-the-art methods. Using 16 simulated
      samples from various studies, including the CAMI 1+2 challenge, ganon2 achieved up to 0.15 higher
      median F1-score in taxonomic binning. In profiling, improvements in the F1-score median are up to
      0.35, keeping a balanced L1-norm error in the abundance estimation. ganon2 is one of the fastest
      tools evaluated and enables the use of larger, more diverse, and up-to-date reference sets in
      daily microbiome analysis, improving the resolution of results. The code is open-source and
      available with documentation at https://github.com/pirovc/ganon.},
     author = {Vitor C. Piro and Knut Reinert},
     booktitle = {ganon2: up-to-date and scalable metagenomics analysis},
     journal = {NAR Genomics and Bioinformatics},
     month = {July},
     number = {3},
     publisher = {Oxford University Press},
     title = {ganon2: up-to-date and scalable metagenomics analysis},
     url = {http://publications.imp.fu-berlin.de/3142/},
     volume = {7},
     year = {2025}
    }
  • Yannek Nowatzky, Francesco Russo, Jan Lisec, Alexander Kister, Knut Reinert, Thilo Muth, Philipp Benner, “FIORA: Local neighborhood-based prediction of compound mass spectra from single fragmentation events”, vol. 16, iss. 1, 2025-03-07.
    cite this publication
    @article{fu_mi_publications3246,
     abstract = {Non-targeted metabolomics holds great promise for advancing precision medicine and
      biomarker discovery. However, identifying compounds from tandem mass spectra remains a challenging
      task due to the incomplete nature of spectral reference libraries. Augmenting these libraries with
      simulated mass spectra can provide the necessary references to resolve unmatched spectra, but
      generating high-quality data is difficult. In this study, we present FIORA, an open-source graph
      neural network designed to simulate tandem mass spectra. Our main contribution lies in utilizing
      the molecular neighborhood of bonds to learn breaking patterns and derive fragment ion
      probabilities. FIORA not only surpasses state-of-the-art fragmentation algorithms, ICEBERG and
      CFM-ID, in prediction quality, but also facilitates the prediction of additional features, such as
      retention time and collision cross section. Utilizing GPU acceleration, FIORA enables rapid
      validation of putative compound annotations and large-scale expansion of spectral reference
      libraries with high-quality predictions.},
     author = {Yannek Nowatzky and Francesco Russo and Jan Lisec and Alexander Kister and Knut Reinert
      and Thilo Muth and Philipp Benner},
     booktitle = {Fiora: Local neighborhood-based prediction of compound mass spectra from single
      fragmentation events},
     journal = {Nature Communications},
     month = {March},
     number = {1},
     publisher = {Springer Nature, London},
     title = {FIORA: Local neighborhood-based prediction of compound mass spectra from single
      fragmentation events},
     url = {http://publications.imp.fu-berlin.de/3246/},
     volume = {16},
     year = {2025}
    }
  • Remy Marcel Schwab, Simon G Gottlieb, Knut Reinert, “TetRex: a novel algorithm for index-accelerated search of highly conserved motifs”, vol. 7, iss. 2, 2025-04-17.
    cite this publication
    @article{fu_mi_publications3284,
     abstract = {The scale of modern datasets has necessitated innovations to solve even the most
      traditional and fundamental of computational problems. Set membership and set cardinality are both
      examples of simple queries that, for large enough datasets, quickly become challenging using
      traditional approaches. Interestingly, we find a need for these innovations within the field of
      biology. Despite the vast differences among living organisms, there exist functions so critical to
      life that they are conserved in the genomes and proteomes across seemingly unrelated species.
      Regular expressions (regexes) can serve as a convenient way to represent these conserved sequences
      compactly. However, despite the strong theoretical foundation and maturity of tools available, the
      state-of-the-art regex search falls short of what is necessary to quickly scan an enormous
      database of biological sequences. In this work, we describe a novel algorithm for regex search
      that reduces the search space by leveraging a recently developed compact data structure for set
      membership, the hierarchical interleaved bloom filter. We show that the runtime of our method
      combined with a traditional search outperforms state-of-the-art tools.},
     author = {Remy Marcel Schwab and Simon G Gottlieb and Knut Reinert},
     journal = {NAR Genomics and Bioinformatics},
     month = {April},
     number = {2},
     publisher = {Oxford University Press},
     title = {TetRex: a novel algorithm for index-accelerated search of highly conserved motifs},
     url = {http://publications.imp.fu-berlin.de/3284/},
     volume = {7},
     year = {2025}
    }
  • Simon G Gottlieb, Knut Reinert, “SeArcH schemes for Approximate stRing mAtching”, vol. 7, iss. 1, 2025-03-18.
    cite this publication
    @article{fu_mi_publications3285,
     abstract = {Finding approximate occurrences of a query in a text using a full-text index is a
      central problem in stringology with many applications, especially in bioinformatics. The recent
      work has shown significant speed-ups by combining bidirectional indices and employing variations
      of search schemes. Search schemes partition a query and describe how to search the resulting parts
      with a given error bound. The performance of search schemes can be approximated by the node count,
      which represents an upper bound of the number of search steps. Finding optimum search schemes is a
      difficult combinatorial optimization problem that becomes hard to solve for four and more errors.
      This paper improves on a few topics important to search scheme based searches: First, we show how
      search schemes can be used to model previously published approximate search strategies such as
      suffix filters, 01*0-seeds, or the pigeonhole principle. This unifies these strategies in the
      search scheme framework, makes them easily comparable and results in novel search schemes that
      allow for any number of errors. Second, we present a search scheme construction heuristic, which
      is on par with optimum search schemes and has a better node count than any known search scheme for
      equal or above four errors. Finally, using the different search schemes, we show that the node
      count measure is not an ideal performance metric and therefore propose an improved performance
      metric called the weighted node count, which approximates a search algorithm?s run time much more
      accurately.},
     author = {Simon G Gottlieb and Knut Reinert},
     journal = {NAR Genomics and Bioinformatics},
     month = {March},
     number = {1},
     publisher = {Oxford University Press},
     title = {SeArcH schemes for Approximate stRing mAtching},
     url = {http://publications.imp.fu-berlin.de/3285/},
     volume = {7},
     year = {2025}
    }
  • Simon G Gottlieb, Knut Reinert, “Engineering rank queries on bit vectors and strings”, vol. 20 / 1, iss. 21, 2025-12-11.
    cite this publication
    @article{fu_mi_publications3312,
     abstract = {Adding rank support to strings over a fixed-sized alphabet has numerous applications.
      Prominent among those is the (bidirectional) FM-Index which is commonly utilized to index and
      analyze genomic data. At its core lies the rank operation on the Burrows-Wheeler-Transform (BWT)
      which, given a position in the BWT and a character, answers how often the specified character
      appears from the start to that position. Implementing those rank queries is usually based on bit
      vectors with rank support. In this work, we discuss three implementation improvements. First, a
      novel approach named paired-blocks that reduces the space overhead of the support structure by
      half to a total of only . Second, a method for masking bits for the population count (also known
      as popcount) which greatly improves the runtime of 512-bit wide blocks in conjunction with AVX512
      SIMD extensions. Third, a revised method for EPR-dictionaries (Pockrandt et al. in International
      conference on research in computational molecular biology. Springer, New York, 2017) called
      flattened bit vectors (fBV) with less space consumption and faster rank operations on strings,
      which is competitive in size and depending on the parameters between and faster than Wavelet Trees
      (Gog et al. in 13th International Symposium on Experimental Algorithms. Springer, New York,
      2014).},
     author = {Simon G Gottlieb and Knut Reinert},
     journal = {Algorithms for Molecular Biology},
     month = {December},
     number = {21},
     title = {Engineering rank queries on bit vectors and strings},
     url = {http://publications.imp.fu-berlin.de/3312/},
     volume = {20 / 1},
     year = {2025}
    }
  • Narges Dadkhah, Somayeh Mohammadi, Gerhard Wunder, “Tuning Block Size for Workload Optimization in Consortium Blockchain Networks”, 2025-08-14.
    cite this publication
    @article{fu_mi_publications3313,
     abstract = {Determining the optimal block size is crucial for achieving high throughput in
      blockchain systems. Many studies have focused on tuning various components, such as databases,
      network bandwidth, and consensus mechanisms. However, the impact of block size on system
      performance remains a topic of debate, often resulting in divergent views and even leading to new
      forks in blockchain networks. This research proposes a mathematical model to maximize performance
      by determining the ideal block size for Hyperledger Fabric, a prominent consortium blockchain. By
      leveraging machine learning and solving the model with a genetic algorithm, the proposed approach
      assesses how factors such as block size, transaction size, and network capacity influence the
      block processing time. The integration of an optimization solver enables precise adjustments to
      block size configuration before deployment, ensuring improved performance from the outset. This
      systematic approach aims to balance block processing efficiency, network latency, and system
      throughput, offering a robust solution to improve blockchain performance across diverse business
      contexts.},
     author = {Narges Dadkhah and Somayeh Mohammadi and Gerhard Wunder},
     journal = {2025 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)},
     month = {August},
     pages = {1--3},
     publisher = {IEEE},
     title = {Tuning Block Size for Workload Optimization in Consortium Blockchain Networks},
     url = {http://publications.imp.fu-berlin.de/3313/},
     year = {2025}
    }
  • Sean R. Wilkinson, Meznah Aloqalaa, Khalid Belhajjame, Michael R. Crusoe, ... et al., “Applying the FAIR Principles to computational workflows”, vol. 12, 2025-02-24.
    cite this publication
    @article{fu_mi_publications3314,
     abstract = {Recent trends within computational and data sciences show an increasing recognition and
      adoption of computational workflows as tools for productivity and reproducibility that also
      democratize access to platforms and processing know-how. As digital objects to be shared,
      discovered, and reused, computational workflows benefit from the FAIR principles, which stand for
      Findable, Accessible, Interoperable, and Reusable. The Workflows Community Initiative?s FAIR
      Workflows Working Group (WCI-FW), a global and open community of researchers and developers
      working with computational workflows across disciplines and domains, has systematically addressed
      the application of both FAIR data and software principles to computational workflows. We present
      recommendations with commentary that reflects our discussions and justifies our choices and
      adaptations. These are offered to workflow users and authors, workflow management system
      developers, and providers of workflow services as guidelines for adoption and fodder for
      discussion. The FAIR recommendations for workflows that we propose in this paper will maximize
      their value as research assets and facilitate their adoption by the wider community.},
     author = {Sean R. Wilkinson and Meznah Aloqalaa and Khalid Belhajjame and Michael R. Crusoe and ...
      et al.},
     journal = {Scientific Data},
     month = {February},
     publisher = {Nature Publ. Group, London},
     title = {Applying the FAIR Principles to computational workflows},
     url = {http://publications.imp.fu-berlin.de/3314/},
     volume = {12},
     year = {2025}
    }
  • Daniel Arend, Daniel Bauer, Sebastian Beier, Marco Brandizi, Dominik Brilhaus, Eli Chadwick, Vera Clemens, Michael R. Crusoe, ... et al., “BioHackEU24 report: Creating user benefit from ARC-ISA RO-Crate machine-actionability & Increasing FAIRness of digital agrosystem resources by extending Bioschemas”, 2025-01-31.
    cite this publication
    @inproceedings{fu_mi_publications3315,
     author = {Daniel Arend and Daniel Bauer and Sebastian Beier and Marco Brandizi and Dominik Brilhaus
      and Eli Chadwick and Vera Clemens and Michael R. Crusoe and ... et al.},
     booktitle = {BioHackrXiv; BioHackathon Europe},
     month = {January},
     title = {BioHackEU24 report: Creating user benefit from ARC-ISA RO-Crate machine-actionability \&
      Increasing FAIRness of digital agrosystem resources by extending Bioschemas},
     url = {http://publications.imp.fu-berlin.de/3315/},
     year = {2025}
    }

2024

  • Chenxu Pan, Knut Reinert, Alfonso Valencia, “A simple refined DNA minimizer operator enables 2-fold faster computation”, vol. 40, iss. 2, 2024-01-25.
    cite this publication
    @article{fu_mi_publications3139,
     abstract = {Motivation The minimizer concept is a data structure for sequence sketching. The
      standard canonical minimizer selects a subset of k-mers from the given DNA sequence by comparing
      the forward and reverse k-mers in a window simultaneously according to a predefined selection
      scheme. It is widely employed by sequence analysis such as read mapping and assembly. k-mer
      density, k-mer repetitiveness (e.g. k-mer bias), and computational efficiency are three critical
      measurements for minimizer selection schemes. However, there exist trade-offs between kinds of
      minimizer variants. Generic, effective, and efficient are always the requirements for
      high-performance minimizer algorithms. Results We propose a simple minimizer operator as a
      refinement of the standard canonical minimizer. It takes only a few operations to compute.
      However, it can improve the k-mer repetitiveness, especially for the lexicographic order. It
      applies to other selection schemes of total orders (e.g. random orders). Moreover, it is
      computationally efficient and the density is close to that of the standard minimizer. The refined
      minimizer may benefit high-performance applications like binning and read mapping. Availability
      and implementation The source code of the benchmark in this work is available at the github
      repository https://github.com/xp3i4/mini\_benchmark},
     author = {Chenxu Pan and Knut Reinert and Alfonso Valencia},
     journal = {Bioinformatics},
     month = {January},
     number = {2},
     publisher = {Oxford University Press},
     title = {A simple refined DNA minimizer operator enables 2-fold faster computation},
     url = {http://publications.imp.fu-berlin.de/3139/},
     volume = {40},
     year = {2024}
    }
  • Mădălina Giurgiu, Nadine Wittstruck, Elias Rodriguez-Fos, RocĂ­o Chamorro GonzĂĄlez, Lotte BrĂŒckner, Annabell Krienelke-Szymansky, Konstantin Helmsauer, Anne Hartebrodt, Philipp Euskirchen, Richard P. Koche, Kerstin Haase, Knut Reinert, Anton G. Henssen, “Decoil: Reconstructing Extrachromosomal DNA Structural Heterogeneity from Long-Read Sequencing Data”, 2024-05-17.
    cite this publication
    @article{fu_mi_publications3141,
     abstract = {Circular extrachromosomal DNA (ecDNA) is a form of oncogene amplification found across
      cancer types and associated with poor outcome in patients. EcDNA can be structurally complex and
      contain rearranged DNA sequences derived from multiple chromosome locations. As the structure of
      ecDNA can impact oncogene regulation and may indicate mechanisms of its formation, disentangling
      it at high resolution from sequencing data is essential. Even though methods have been developed
      to identify and reconstruct ecDNA in cancer genome sequencing, it remains challenging to resolve
      complex ecDNA structures, in particular amplicons with shared genomic footprints. We here
      introduce Decoil, a computational method which combines a breakpoint-graph approach with LASSO
      regression to reconstruct complex ecDNA and deconvolve co-occurring ecDNA elements with
      overlapping genomic footprints from long-read nanopore sequencing. Decoil outperforms de-novo
      assembly and alignment-based methods in simulated long-read sequencing data for both simple and
      complex ecDNAs. Applying Decoil on whole genome sequencing data uncovered different ecDNA
      topologies and explored ecDNA structure heterogeneity in neuroblastoma tumors and cell lines,
      indicating that this method may improve ecDNA structural analyzes in cancer.},
     author = {M{\u a}d{\u a}lina Giurgiu and Nadine Wittstruck and Elias Rodriguez-Fos and Roc{\'i}o
      Chamorro Gonz{\'a}lez and Lotte Br{\"u}ckner and Annabell Krienelke-Szymansky and Konstantin
      Helmsauer and Anne Hartebrodt and Philipp Euskirchen and Richard P. Koche and Kerstin Haase and
      Knut Reinert and Anton G. Henssen},
     booktitle = {Decoil: Reconstructing extrachromosomal DNA structural heterogeneity from long-read
      sequencing data},
     journal = {Research in Computational Molecular Biology (RECOMB 2024)},
     month = {May},
     pages = {406--411},
     publisher = {Springer, Cham},
     title = {Decoil: Reconstructing Extrachromosomal DNA Structural Heterogeneity from Long-Read
      Sequencing Data},
     url = {http://publications.imp.fu-berlin.de/3141/},
     year = {2024}
    }
  • Hannes Hauswedell, Sara Hetzel, Simon G Gottlieb, Helene Kretzmer, Alexander Meissner, Knut Reinert, Lenore Cowen, “Lambda3: homology search for protein, nucleotide, and bisulfite-converted sequences”, vol. 40, iss. 3, 2024-03-14.
    cite this publication
    @article{fu_mi_publications3143,
     abstract = {Motivation Local alignments of query sequences in large databases represent a core part
      of metagenomic studies and facilitate homology search. Following the development of NCBI Blast,
      many applications aimed to provide faster and equally sensitive local alignment frameworks. Most
      applications focus on protein alignments, while only few also facilitate DNA-based searches. None
      of the established programs allow searching DNA sequences from bisulfite sequencing experiments
      commonly used for DNA methylation profiling, for which specific alignment strategies need to be
      implemented. Results Here, we introduce Lambda3, a new version of the local alignment application
      Lambda. Lambda3 is the first solution that enables the search of protein, nucleotide as well as
      bisulfite-converted nucleotide query sequences. Its protein mode achieves comparable performance
      to that of the highly optimized protein alignment application Diamond, while the nucleotide mode
      consistently outperforms established local nucleotide aligners. Combined, Lambda3 presents a
      universal local alignment framework that enables fast and sensitive homology searches for a wide
      range of use-cases. Availability and implementation Lambda3 is free and open-source software
      publicly available at https://github.com/seqan/lambda/.},
     author = {Hannes Hauswedell and Sara Hetzel and Simon G Gottlieb and Helene Kretzmer and Alexander
      Meissner and Knut Reinert and Lenore Cowen},
     journal = {Bioinformatics},
     month = {March},
     number = {3},
     publisher = {Oxford University Press},
     title = {Lambda3: homology search for protein, nucleotide, and bisulfite-converted sequences},
     url = {http://publications.imp.fu-berlin.de/3143/},
     volume = {40},
     year = {2024}
    }
  • Somayeh Mohammadi, Latif PourKarimi, Manuel ZschĂ€bitz, Tristan Aretz, Ninon De Mecquenem, Ulf Leser, Knut Reinert, “Optimizing Job/Task Granularity for Metagenomic Workflows in Heterogeneous Cluster Infrastructures”, 2024-03-25.
    cite this publication
    @inproceedings{fu_mi_publications3144,
     abstract = {Data analysis workflows are popular for sequencing activities in large-scale and
      complex scientific processes. Scheduling approaches attempt to find an appropriate assignment of
      workflow tasks to the computing nodes for minimizing the makespan in heterogeneous cluster
      infrastructures. A common feature of these approaches is that they already know the structure of
      the workflow. However, for many workflows, a high degree of parallelization can be achieved by
      splitting the large input data of a single task into chunks and processing them independently. We
      call this problem task granularity, which involves finding an assignment of tasks to computing
      nodes and simultaneously optimizing the structure of a bag of tasks. Accordingly, this paper
      addresses the problem of task granularity for metagenomic workflows. To this end, we first
      formulated the problem as a mathematical model. We then solved the proposed model using the
      genetic algorithm. To overcome the challenge of not knowing the number of tasks, we adjusted the
      number of tasks as a factor of the number of computing nodes. The procedure of increasing the
      number of tasks is performed interactively and evolutionarily. Experimental results showed that a
      desirable makespan value can be achieved after a few steps of the increase.},
     author = {Somayeh Mohammadi and Latif PourKarimi and Manuel Zsch{\"a}bitz and Tristan Aretz and
      Ninon De Mecquenem and Ulf Leser and Knut Reinert},
     booktitle = {EDBT/ICDT 2024 Joint Conference: 8th International workshop on Data Analytics
      solutions for Real-LIfe APplications (DARLI-AP)},
     month = {March},
     title = {Optimizing Job/Task Granularity for Metagenomic Workflows in Heterogeneous Cluster
      Infrastructures},
     url = {http://publications.imp.fu-berlin.de/3144/},
     year = {2024}
    }
  • Ninon De Mecquenem, Simon Bosse, Vasilis Bountris, Somayeh Mohammadi, Knut Reinert, Ulf Leser, “CuttleFlow: Infrastructure-Specific Workflow Adaption for Improved Reusability”, 2024-09-20.
    cite this publication
    @inproceedings{fu_mi_publications3243,
     abstract = {Scientific workflows have gained popularity for large-scale data analysis due to their
      potential to improve the reproducibility, scalability and documentation of complex multistep
      scientific analysis pipelines. However, their reusability is currently limited in practice, as a
      workflow is typically developed for a specific infrastructure. This is reflected in the choice of
      tools (e.g. less/more memory requirements), their configuration (e.g. number of threads) and the
      workflow topology (e.g. data parallel scatter/gather). Re-running such a workflow requires access
      to the same, or at least a highly similar, computing environment, effectively reducing its use by
      other groups. To address this challenge, we present CuttleFlow, a novel method for adapting and
      rewriting scientific workflows given a description of an infrastructure and its inputs. CuttleFlow
      starts from an abstract workflow description and compiles it into an infrastructure-specific
      logical workflow using three types of rewriting operations, namely tool replacement, tool
      reconfiguration, and data scattering/gathering for task parallelization. We implement a prototype
      based on NextFlow and evaluate it for two important bioinformatics data analysis problems, namely
      RNAseq and metagenomics, on a distributed infrastructure. We demonstrate the large impact that the
      rewriting of CuttleFlow can have on runtime, achieving a reduction in makespan of up to 71\%. We
      also demonstrate a significant reduction in resource usage through our rewriting approach.},
     author = {Ninon De Mecquenem and Simon Bosse and Vasilis Bountris and Somayeh Mohammadi and Knut
      Reinert and Ulf Leser},
     booktitle = {2024 IEEE 20th International Conference on e-Science (e-Science)},
     month = {September},
     pages = {1--10},
     title = {CuttleFlow: Infrastructure-Specific Workflow Adaption for Improved Reusability},
     url = {http://publications.imp.fu-berlin.de/3243/},
     year = {2024}
    }
  • Mădălina Giurgiu, Nadine Wittstruck, Elias Rodriguez-Fos, RocĂ­o Chamorro GonzĂĄlez, Lotte BrĂŒckner, Annabell Krienelke-Szymansky, Konstantin Helmsauer, Anne Hartebrodt, Philipp Euskirchen, Richard P. Koche, Kerstin Haase, Knut Reinert, Anton G. Henssen, “Reconstructing extrachromosomal DNA structural heterogeneity from long-read sequencing data using Decoil”, vol. 34, iss. 9, 2024-08-07.
    cite this publication
    @article{fu_mi_publications3244,
     abstract = {Circular extrachromosomal DNA (ecDNA) is a form of oncogene amplification found across
      cancer types and associated with poor outcome in patients. ecDNA can be structurally complex and
      can contain rearranged DNA sequences derived from multiple chromosome locations. As the structure
      of ecDNA can impact oncogene regulation and may indicate mechanisms of its formation,
      disentangling it at high resolution from sequencing data is essential. Even though methods have
      been developed to identify and reconstruct ecDNA in cancer genome sequencing, it remains
      challenging to resolve complex ecDNA structures, in particular amplicons with shared genomic
      footprints. We here introduce Decoil, a computational method that combines a breakpoint-graph
      approach with LASSO regression to reconstruct complex ecDNA and deconvolve co-occurring ecDNA
      elements with overlapping genomic footprints from long-read nanopore sequencing. Decoil
      outperforms de novo assembly and alignment-based methods in simulated long-read sequencing data
      for both simple and complex ecDNAs. Applying Decoil on whole-genome sequencing data uncovered
      different ecDNA topologies and explored ecDNA structure heterogeneity in neuroblastoma tumors and
      cell lines, indicating that this method may improve ecDNA structural analyses in cancer.},
     author = {M{\u a}d{\u a}lina Giurgiu and Nadine Wittstruck and Elias Rodriguez-Fos and Roc{\'i}o
      Chamorro Gonz{\'a}lez and Lotte Br{\"u}ckner and Annabell Krienelke-Szymansky and Konstantin
      Helmsauer and Anne Hartebrodt and Philipp Euskirchen and Richard P. Koche and Kerstin Haase and
      Knut Reinert and Anton G. Henssen},
     journal = {Genome Research},
     month = {August},
     number = {9},
     pages = {1355--1364},
     publisher = {Cold Spring Harbor Laboratory Press},
     title = {Reconstructing extrachromosomal DNA structural heterogeneity from long-read sequencing
      data using Decoil},
     url = {http://publications.imp.fu-berlin.de/3244/},
     volume = {34},
     year = {2024}
    }
  • Chenxu Pan, Knut Reinert, “Leaf: an ultrafast filter for population-scale long-read SV detection”, vol. 25, iss. 1, 2024-06-13.
    cite this publication
    @article{fu_mi_publications3245,
     abstract = {Advances in sequencing technology have facilitated population-scale long-read
      structural variant (SV) detection. Arguably, one of the main challenges in population-scale
      analysis is developing effective computational pipelines. Here, we present a new filter-based
      pipeline for population-scale long-read SV detection. It better captures SV signals at an early
      stage than conventional assembly-based or alignment-based pipelines. Assessments in this work
      suggest that the filter-based pipeline helps better resolve intra-read rearrangements. Moreover,
      it is also more computationally efficient than conventional pipelines and thus may facilitate
      population-scale long-read applications.},
     author = {Chenxu Pan and Knut Reinert},
     journal = {Genome Biology},
     month = {June},
     number = {1},
     pages = {Artikel 155 --(18 Seiten)},
     publisher = {BioMed Central},
     title = {Leaf: an ultrafast filter for population-scale long-read SV detection},
     url = {http://publications.imp.fu-berlin.de/3245/},
     volume = {25},
     year = {2024}
    }
  • Chenxu Pan, “High-performance algorithms and applications of long-read mapping and SV detection”, 2024.
    cite this publication
    @phdthesis{fu_mi_publications3283,
     abstract = {Advances in sequencing technology have facilitated population-scale long-read analysis,
      in which one of the main challenges is arguably developing high-performance computational
      pipelines. Sequence alignment and assembly are two main long-read analysis methods.
      Alignment-based pipelines are commonly more efficient and require less read coverage than
      assembly-based ones, and thus are more applicable to population-scale analysis. However,
      alignment-based pipelines are less effective in reconstructing highly diverse structures in
      ultra-long reads such as intra-read SVs. Here, we propose a new filter-based pipeline that is
      designed to capture rearrangement signals at an earlier stage than conventional pipelines to
      improve long-read analysis performance. To this end, we investigated the feasibility and essential
      methods of the design and assessed the performance of the pipeline. Correspondingly, this work
      comprises three parts starting with data structure optimizations then module development and
      finally large-scale assessments. Assessments based on high-quality datasets suggest that
      filter-based pipelines are comparable to or outperform conventional pipelines in terms of
      detecting complex intra-read rearrangements and computational efficiency. Therefore, the newly
      proposed pipeline may further benefit population-scale long-read analysis.},
     author = {Chenxu Pan},
     school = {Freie Universit{\"a}t Berlin},
     title = {High-performance algorithms and applications of long-read mapping and SV detection},
     url = {http://publications.imp.fu-berlin.de/3283/},
     year = {2024}
    }

2023

  • Svenja Mehringer, Enrico Seiler, Felix Droop, Mitra Darvish, RenĂ© Rahn, Martin Vingron, Knut Reinert, “Hierarchical Interleaved Bloom Filter: enabling ultrafast, approximate sequence queries”, vol. 24, iss. 131, 2023-05-31.
    cite this publication
    @article{fu_mi_publications2846,
     abstract = {We present a novel data structure for searching sequences in large databases: the
      Hierarchical Interleaved Bloom Filter (HIBF). It is extremely fast and space efficient, yet so
      general that it could serve as the underlying engine for many applications. We show that the HIBF
      is superior in build time, index size, and search time while achieving a comparable or better
      accuracy compared to other state-of-the-art tools. The HIBF builds an index up to 211 times
      faster, using up to 14 times less space, and can answer approximate membership queries faster by a
      factor of up to 129. We show that the HIBF is superior in build time, index size and search time
      while achieving a comparable or better accuracy compared to other state-of-the art tools (Mantis
      and Bifrost). The HIBF builds an index up to 211 times faster, using up to 14 times less space and
      can answer approximate membership queries faster by a factor of up to 129. This can be considered
      a quantum leap that opens the door to indexing complete sequence archives like the European
      Nucleotide Archive or even larger metagenomics data sets.},
     author = {Svenja Mehringer and Enrico Seiler and Felix Droop and Mitra Darvish and Ren{\'e} Rahn
      and Martin Vingron and Knut Reinert},
     booktitle = {Hierarchical Interleaved Bloom Filter: Enabling ultrafast, approximate sequence
      queries},
     journal = {Genome Biology},
     month = {May},
     number = {131},
     publisher = {BioMed Central},
     title = {Hierarchical Interleaved Bloom Filter: enabling ultrafast, approximate sequence queries},
     url = {http://publications.imp.fu-berlin.de/2846/},
     volume = {24},
     year = {2023}
    }
  • Yannek Nowatzky, Philipp Benner, Knut Reinert, Thilo Muth, “Mistle: bringing spectral library predictions to metaproteomics with an efficient search index”, vol. 39, iss. 6, 2023-09-09.
    cite this publication
    @article{fu_mi_publications2946,
     abstract = {Motivation Deep learning has moved to the forefront of tandem mass spectrometry-driven
      proteomics and authentic prediction for peptide fragmentation is more feasible than ever. Still,
      at this point spectral prediction is mainly used to validate database search results or for
      confined search spaces. Fully predicted spectral libraries have not yet been efficiently adapted
      to large search space problems that often occur in metaproteomics or proteogenomics. Results In
      this study, we showcase a workflow that uses Prosit for spectral library predictions on two common
      metaproteomes and implement an indexing and search algorithm, Mistle, to efficiently identify
      experimental mass spectra within the library. Hence, the workflow emulates a classic protein
      sequence database search with protein digestion but builds a searchable index from spectral
      predictions as an in-between step. We compare Mistle to popular search engines, both on a spectral
      and database search level, and provide evidence that this approach is more accurate than a
      database search using MSFragger. Mistle outperforms other spectral library search engines in terms
      of run time and proves to be extremely memory efficient with a 4- to 22-fold decrease in RAM
      usage. This makes Mistle universally applicable to large search spaces, e.g. covering
      comprehensive sequence databases of diverse microbiomes. Availability and implementation Mistle is
      freely available on GitHub at https://github.com/BAMeScience/Mistle.},
     author = {Yannek Nowatzky and Philipp Benner and Knut Reinert and Thilo Muth},
     booktitle = {Mistle: bringing spectral library predictions to metaproteomics with an efficient
      search index},
     journal = {Bioinformatics},
     month = {September},
     number = {6},
     publisher = {Oxford University Press},
     title = {Mistle: bringing spectral library predictions to metaproteomics with an efficient search
      index},
     url = {http://publications.imp.fu-berlin.de/2946/},
     volume = {39},
     year = {2023}
    }
  • Chenxu Pan, RenĂ© Rahn, David Heller, Knut Reinert, “Linear: a framework to enable existing software to resolve structural variants in long reads with flexible and efficient alignment-free statistical models”, vol. 24, iss. 2, 2023-03-03.
    cite this publication
    @article{fu_mi_publications2947,
     abstract = {Alignment is the cornerstone of many long-read pipelines and plays an essential role in
      resolving structural variants (SVs). However, forced alignments of SVs embedded in long reads,
      inflexibility of integrating novel SVs models and computational inefficiency remain problems.
      Here, we investigate the feasibility of resolving long-read SVs with alignment-free algorithms. We
      ask: (1) Is it possible to resolve long-read SVs with alignment-free approaches? and (2) Does it
      provide an advantage over existing approaches? To this end, we implemented the framework named
      Linear, which can flexibly integrate alignment-free algorithms such as the generative model for
      long-read SV detection. Furthermore, Linear addresses the problem of compatibility of
      alignment-free approaches with existing software. It takes as input long reads and outputs
      standardized results existing software can directly process. We conducted large-scale assessments
      in this work and the results show that the sensitivity, and flexibility of Linear outperform
      alignment-based pipelines. Moreover, the computational efficiency is orders of magnitude faster.},
     author = {Chenxu Pan and Ren{\'e} Rahn and David Heller and Knut Reinert},
     journal = {Briefings in Bioinformatics},
     keywords = {alignment-free approach, graph generative model, structural variants resolution,
      long-read analysis},
     month = {March},
     number = {2},
     publisher = {Oxford University Press},
     title = {Linear: a framework to enable existing software to resolve structural variants in long
      reads with flexible and efficient alignment-free statistical models},
     url = {http://publications.imp.fu-berlin.de/2947/},
     volume = {24},
     year = {2023}
    }
  • Yuwei Wang, Bin Lian, Haohui Zhang, Yuanke Zhong, Jie He, Fashuai Wu, Knut Reinert, Xuequn Shang, Hui Yang, Jialu Hu, Anthony Mathelier, “A multi-view latent variable model reveals cellular heterogeneity in complex tissues for paired multimodal single-cell data”, vol. 39, iss. 1, 2023-01-09.
    cite this publication
    @article{fu_mi_publications2948,
     abstract = {Motivation: Single-cell multimodal assays allow us to simultaneously measure two
      different molecular features of the same cell, enabling new insights into cellular heterogeneity,
      cell development and diseases. However, most existing methods suffer from inaccurate
      dimensionality reduction for the joint-modality data, hindering their discovery of novel or rare
      cell subpopulations. Results: Here, we present VIMCCA, a computational framework based on
      variational-assisted multi-view canonical correlation analysis to integrate paired multimodal
      single-cell data. Our statistical model uses a common latent variable to interpret the common
      source of variances in two different data modalities. Our approach jointly learns an inference
      model and two modality-specific non-linear models by leveraging variational inference and deep
      learning. We perform VIMCCA and compare it with 10 existing state-of-the-art algorithms on four
      paired multi-modal datasets sequenced by different protocols. Results demonstrate that VIMCCA
      facilitates integrating various types of joint-modality data, thus leading to more reliable and
      accurate downstream analysis. VIMCCA improves our ability to identify novel or rare cell subtypes
      compared to existing widely used methods. Besides, it can also facilitate inferring cell lineage
      based on joint-modality profiles. Availability and implementation: The VIMCCA algorithm has been
      implemented in our toolkit package scbean (??0.5.0), and its code has been archived at
      https://github.com/jhu99/scbean under MIT license.},
     author = {Yuwei Wang and Bin Lian and Haohui Zhang and Yuanke Zhong and Jie He and Fashuai Wu and
      Knut Reinert and Xuequn Shang and Hui Yang and Jialu Hu and Anthony Mathelier},
     journal = {Bioinformatics},
     month = {January},
     number = {1},
     publisher = {Oxford University Press},
     title = {A multi-view latent variable model reveals cellular heterogeneity in complex tissues for
      paired multimodal single-cell data},
     url = {http://publications.imp.fu-berlin.de/2948/},
     volume = {39},
     year = {2023}
    }
  • Vitor C Piro, Bernhard Y Renard, “Contamination detection and microbiome exploration with GRIMER”, vol. 12, 2023-03-30.
    cite this publication
    @article{fu_mi_publications2949,
     abstract = {Background: Contamination detection is a important step that should be carefully
      considered in early stages when designing and performing microbiome studies to avoid biased
      outcomes. Detecting and removing true contaminants is challenging, especially in low-biomass
      samples or in studies lacking proper controls. Interactive visualizations and analysis platforms
      are crucial to better guide this step, to help to identify and detect noisy patterns that could
      potentially be contamination. Additionally, external evidence, like aggregation of several
      contamination detection methods and the use of common contaminants reported in the literature,
      could help to discover and mitigate contamination. Results: We propose GRIMER, a tool that
      performs automated analyses and generates a portable and interactive dashboard integrating
      annotation, taxonomy, and metadata. It unifies several sources of evidence to help detect
      contamination. GRIMER is independent of quantification methods and directly analyzes contingency
      tables to create an interactive and offline report. Reports can be created in seconds and are
      accessible for nonspecialists, providing an intuitive set of charts to explore data distribution
      among observations and samples and its connections with external sources. Further, we compiled and
      used an extensive list of possible external contaminant taxa and common contaminants with 210
      genera and 627 species reported in 22 published articles. Conclusion: GRIMER enables visual data
      exploration and analysis, supporting contamination detection in microbiome studies. The tool and
      data presented are open source and available at https://gitlab.com/dacs-hpi/grimer.},
     author = {Vitor C Piro and Bernhard Y Renard},
     journal = {GigaScience},
     month = {March},
     publisher = {Oxford University Press},
     title = {Contamination detection and microbiome exploration with GRIMER},
     url = {http://publications.imp.fu-berlin.de/2949/},
     volume = {12},
     year = {2023}
    }
  • Somayeh Mohammadi, Latif PourKarimi, Felix Droop, Ninon De Mecquenem, Ulf Leser, Knut Reinert, “A mathematical programming approach for resource allocation of data analysis workflows on heterogeneous clusters”, vol. 79, iss. 17, 2023-03-23.
    cite this publication
    @article{fu_mi_publications3140,
     abstract = {Scientific communities are motivated to schedule their large-scale data analysis
      workflows in heterogeneous cluster environments because of privacy and financial issues. In such
      environments containing considerably diverse resources, efficient resource allocation approaches
      are essential for reaching high performance. Accordingly, this research addresses the scheduling
      problem of workflows with bag-of-task form to minimize total runtime (makespan). To this aim, we
      develop a mixed-integer linear programming model (MILP). The proposed model contains binary
      decision variables determining which tasks should be assigned to which nodes. Also, it contains
      linear constraints to fulfill the tasks requirements such as memory and scheduling policy.
      Comparative results show that our approach outperforms related approaches in most cases. As part
      of the post-optimality analysis, some secondary preferences are imposed on the proposed model to
      obtain the most preferred optimal solution. We analyze the relaxation of the makespan in the hope
      of significantly reducing the number of consumed nodes.},
     author = {Somayeh Mohammadi and Latif PourKarimi and Felix Droop and Ninon De Mecquenem and Ulf
      Leser and Knut Reinert},
     journal = {The Journal of Supercomputing},
     month = {March},
     number = {17},
     pages = {19019--19048},
     publisher = {Springer},
     title = {A mathematical programming approach for resource allocation of data analysis workflows on
      heterogeneous clusters},
     url = {http://publications.imp.fu-berlin.de/3140/},
     volume = {79},
     year = {2023}
    }
  • Sara Hetzel, “Investigation of DNA methylation heterogeneity in cancer”, 2023.
    cite this publication
    @phdthesis{fu_mi_publications3249,
     abstract = {Within the body, every cell contains the same genetic blueprint, the DNA, which is
      wrapped around histones and densely packed in the nucleus. Given the same genome, the identity of
      each cell is in part defined by modifications to the histones but also the genomic sequence
      itself, such as DNA methylation, that define active and inactive parts of the DNA. In somatic
      cells, DNA methylation levels are largely bimodal, with a high genome-wide methylation average
      that predominantly excludes CpG islands (CGIs), features often found near gene promoters that
      remain free of methylation. These patterns change across the majority of human cancer types, which
      exhibit global loss of methylation accompanied by a gain of methylation at select CGIs. To date,
      bisulfite sequencing represents the gold-standard method to profile DNA methylation at single-base
      resolution and has been widely used to characterize and understand DNA methylation landscapes in
      healthy and tumor cells. This thesis presents advancements in the computational analysis of
      bisulfite sequencing data sets, as well as applications to large-scale studies of DNA methylation
      in cancer. It showcases the adaptation of a local alignment tool to enable homology search for
      bisulfite-converted sequences, which outperforms established semi-global alignment tools when
      applied to the search of metagenomic data sets. Additionally, this thesis describes the
      development of a new application that provides fast and simplified extraction of DNA methylation
      heterogeneity metrics from single reads of bisulfite sequencing data. The importance of such
      metrics is demonstrated in the context of two studies that focus on DNA methylation changes within
      primary tumors and cancer cell lines. Single-read metrics and single-cell methylome profiling show
      that primary tumors are mainly characterized by heterogeneous, intermediate global and CGI DNA
      methylation that is intrinsic to the underlying single tumor cells. In contrast, cancer cell lines
      mostly assume one of two different states, where global DNA methylation levels are either
      drastically decreased or comparable to healthy tissues, while CGIs become almost fully methylated
      in both scenarios. Although rarely seen in solid tumors, extremely high genome-wide methylation
      levels can also be observed in an exceptional primary tumor type, acute lymphoblastic leukemia,
      where this landscape is influenced by specific epigenetic regulators. Together, the findings of
      this thesis advance our ability to analyze bisulfite sequencing data sets as well as to apply
      these more nuanced measurements to understand DNA methylation changes during tumorigenesis and in
      culture.},
     author = {Sara Hetzel},
     school = {Freie Universit{\"a}t Berlin},
     title = {Investigation of DNA methylation heterogeneity in cancer},
     url = {http://publications.imp.fu-berlin.de/3249/},
     year = {2023}
    }
  • Jörg Winkler, “Algorithms for finding RNA sequence-structure motifs”, 2023.
    cite this publication
    @phdthesis{fu_mi_publications3250,
     abstract = {The function of non-coding RNA sequences is largely determined by their spatial
      conformation. This is the secondary structure of the molecule, which is formed by Watson?Crick
      interactions between nucleotides. Hence, modern RNA alignment algorithms routinely take structural
      information into account. Essential tasks for discovering yet unknown RNA families and inferring
      their possible functions are the structural alignment of RNAs and the subsequent search of the
      derived structural motifs. These tasks demand a lot of computational resources, especially for
      aligning many long sequences, and it therefore requires efficient algorithms that utilize modern
      hardware when available. A subset of the secondary structures contains pseudoknots, which are
      overlapping interactions that add additional complexity to the analysis and are often ignored in
      available software. In this thesis, I present LaRA 2 and MaRs, two SeqAn-based software tools that
      implement algorithms for finding sequence-structure motifs in genomic sequences. In contrast to
      other programs, my tools can handle arbitrary pseudoknots. They use multithreading for parallel
      execution and are implemented in modern C++ code for maximal longevity and performance. LaRA2 is
      significantly faster than comparable software for accurate pairwise and multiple alignments of
      structured RNA sequences. It uses a new heuristic for computing a lower boundary to the solution
      and employs vectorization techniques for speeding up the time-critical parts of the algorithm.
      MaRs can be applied in a workflow right after LaRA2 and derives sequence-structure motifs from the
      structural alignments. The motifs are descriptors of the RNA sequences? properties and drive the
      search for homologs in genomic sequences. MaRs employs a bidirectional index on the genomic
      sequences and an optimized multithreaded search strategy for finding the matches really fast. The
      use of a thread pool, effective pruning strategies, and a low memory footprint ensure that MaRs is
      capable of processing extremely large data sets.},
     author = {J{\"o}rg Winkler},
     school = {Freie Universit{\"a}t Berlin},
     title = {Algorithms for finding RNA sequence-structure motifs},
     url = {http://publications.imp.fu-berlin.de/3250/},
     year = {2023}
    }
  • RenĂ© Rahn, “Performance-Driven Algorithm Engineering”, 2023.
    cite this publication
    @phdthesis{fu_mi_publications3251,
     abstract = {A number of technological advancements in high-throughput genome sequencing have led to
      the generation of exabyte-scale sequencing data worldwide in recent years. These developments have
      facilitated large-scale resequencing projects like the 1000 Genomes Project, which aim to catalog
      the genetic diversity of organisms and speci?c populations. In the context of medical research,
      incorporating population data, is of particular interest. However, existing applications are often
      optimised for analysing a few sequences, and the methods used cannot be easily transferred to
      these vast datasets without exceeding system resources or producing results within a suitable time
      frame. Simultaneously, the execution model of processors has evolved from sequential to highly
      parallel process execution, thanks to the addition of processor cores, vector processing units,
      and advances in superscalar processor designs. This ongoing development in high-performance
      computing requires applications and algorithms to scale with the growing levels of parallelism.
      However, highly optimised algorithms are often embedded within applications, making them
      practically inaccessible to the scienti?c community. In this dissertation, we ?rst investigate a
      generic approach to parallelise and vectorise pairwise sequence alignments using a dynamically
      scalable concurrency model. We explore various techniques and code-level optimisations to
      effectively utilise the available parallelisms on modern high-performance CPUs. The results
      demonstrate that the dynamically accelerated pairwise sequence alignment scales proportionally
      with the number of cores and provides speed-ups of up to a factor of 2500 compared to the
      sequential reference implementation on modern hardware. Second, we propose a general solution for
      data-compressed acceleration of pattern matching algorithms by compressing a large collection of
      related DNA sequences and providing a set of composable algorithms to re?ne and optimise the
      applicable operations. Our research on data-compressed acceleration shows hundred-fold speed-ups
      for online searching over a pangenome comprising over 5000 reference sequences compared to the
      naive approach of individually searching all sequences. These speed-ups are achieved while
      utilising only a fraction of the main memory. Moreover, we implemented these features in dedicated
      modules of the open-source software library SeqAn (https://www.seqan.de/), making them accessible
      and adoptable by the entire research community. While doing so, we strived for a user-friendly API
      design so that these methods can be easily customised and extended, making them applicable to a
      wide range of applications in the domain of computational sequence analysis.},
     author = {Ren{\'e} Rahn},
     school = {Freie Universit{\"a}t Berlin},
     title = {Performance-Driven Algorithm Engineering},
     url = {http://publications.imp.fu-berlin.de/3251/},
     year = {2023}
    }
  • Mitra Darvish, “Utilizing alignment-free methods to enable quantitative gene expression analysis of large collections of sequencing data”, 2023.
    cite this publication
    @phdthesis{fu_mi_publications3252,
     abstract = {Due to advances in sequencing technologies, the amount of sequencing data is
      continuously increasing and has reached an amount that calls for new data management methods, to
      actually utilize the sequencing data. In the last years, a number of different indices haven been
      developed to simplify the data, thereby reducing the amount of space needed and enabling analysis
      on large collections of sequencing data. In this thesis, the index Needle will be introduced,
      which allows (semi-)quantitative analyses on large data sets and outperforms other existing
      solutions with regards to both space and speed. Needle, like other indices, is based on
      alignment-free methods because in this way the costly step of classical sequence analyses, the
      alignment, can be omitted. Alignment-free methods are based on short subsequences of the actual
      sequence data. There are multiple different methods to determine these subsequences and this
      thesis provides a detailed analysis and comparison to determine the best method for such indices.
      Moreover, the benchmarking application minions is introduced, which will make comparisons between
      these methods easier as adding future new methods is simple. Needle is capable of utilizing large
      collections of sequencing data and determining their gene expressions. Three analyses are
      performed, which act as a proof of concept for how Needle can be utilized for large collections of
      sequencing data. Therefore, Needle is applied in this thesis to find cancer signatures, a newly
      annotated mouse transcript and tissue specific differentially expressed genes for different large
      data sets. In summary, indices like Needle are needed to actually take advantage of the data
      wealth currently present in the biological and medical research field.},
     author = {Mitra Darvish},
     school = {Freie Universit{\"a}t Berlin},
     title = {Utilizing alignment-free methods to enable quantitative gene expression analysis of large
      collections of sequencing data},
     url = {http://publications.imp.fu-berlin.de/3252/},
     year = {2023}
    }

2022

  • F. Meyer, A. Fritz, Z.-L. Deng, D. Koslicki, A. Gurevich, G. Robertson, M. Alser, D. Antipov, F. Beghini, D. Bertrand, J. J. Brito, C.T. Brown, J. Buchmann, A. Buluç, B. Chen, R. Chikhi, P. T. Clausen, A. Cristian, P. W. Dabrowski, A. E. Darling, R. Egan, E. Eskin, E. Georganas, E. Goltsman, M. A. Gray, L. H. Hansen, S. Hofmeyr, P. Huang, L. Irber, H. Jia, T. S. JĂžrgensen, S. D. Kieser, T. Klemetsen, A. Kola, M. Kolmogorov, A. Korobeynikov, J. Kwan, N. LaPierre, C. Lemaitre, C. Li, A. Limasset, F. Malcher-Miranda, S. Mangul, V. R. Marcelino, C. Marchet, P. Marijon, D. Meleshko, D. R. Mende, A. Milanese, N. Nagarajan, J. Nissen, S. Nurk, L. Oliker, L. Paoli, P. Peterlongo, V. C. Piro, J. S. Porter, S. Rasmussen, E. R. Rees, K. Reinert, B. Renard, E. M. Robertsen, G. L. Rosen, H.-J. Ruscheweyh, V. Sarwal, N. Segata, E. Seiler, L. Shi, F. Sun, S. Sunagawa, S. J. SĂžrensen, A. Thomas, C. Tong, M. Trajkovski, J. Tremblay, G. Uritskiy, R. Vicedomini, Zi. Wang, Zhe. Wang, Zho. Wang, A. Warren, N. P. Willassen, K. Yelick, R. You, G. Zeller, Z. Zhao, S. Zhu, J. Zhu, R. Garrido-Oter, P. Gastmeier, S. Hacquard, S. HĂ€ußler, A. Khaledi, F. Maechler, F. Mesny, S. Radutoiu, P. Schulze-Lefert, N. Smit, T. Strowig, A. Bremges, A. Sczyrba, A. C. McHardy, “Critical Assessment of Metagenome Interpretation - the second round of challenges”, vol. 19, iss. 4, 2022-04-08.
    cite this publication
    @article{fu_mi_publications2605,
     abstract = {Evaluating metagenomic software is key for optimizing metagenome interpretation and
      focus of the community-driven initiative for the Critical Assessment of Metagenome Interpretation
      (CAMI). In its second challenge, CAMI engaged the community to assess their methods on realistic
      and complex metagenomic datasets with long and short reads, created from {$\sim$}1,700 novel and
      known microbial genomes, as well as {$\sim$}600 novel plasmids and viruses. Altogether 5,002
      results by 76 program versions were analyzed, representing a 22x increase in results. Substantial
      improvements were seen in metagenome assembly, some due to using long-read data. The presence of
      related strains still was challenging for assembly and genome binning, as was assembly quality for
      the latter. Taxon profilers demonstrated a marked maturation, with taxon profilers and binners
      excelling at higher bacterial taxonomic ranks, but underperforming for viruses and archaea.
      Assessment of clinical pathogen detection techniques revealed a need to improve reproducibility.
      Analysis of program runtimes and memory usage identified highly efficient programs, including some
      top performers with other metrics. The CAMI II results identify current challenges, but also guide
      researchers in selecting methods for specific analyses. Competing Interest Statement: A.E.D.
      co-founded Longas Technologies Pty Ltd, a company aimed at development of synthetic long-read
      sequencing technologies.},
     author = {F. Meyer and A. Fritz and Z.-L. Deng and D. Koslicki and A. Gurevich and G. Robertson and
      M. Alser and D. Antipov and F. Beghini and D. Bertrand and J. J. Brito and C.T. Brown and J.
      Buchmann and A. Bulu{\c c} and B. Chen and R. Chikhi and P. T. Clausen and A. Cristian and P. W.
      Dabrowski and A. E. Darling and R. Egan and E. Eskin and E. Georganas and E. Goltsman and M. A.
      Gray and L. H. Hansen and S. Hofmeyr and P. Huang and L. Irber and H. Jia and T. S. J{\o}rgensen
      and S. D. Kieser and T. Klemetsen and A. Kola and M. Kolmogorov and A. Korobeynikov and J. Kwan
      and N. LaPierre and C. Lemaitre and C. Li and A. Limasset and F. Malcher-Miranda and S. Mangul and
      V. R. Marcelino and C. Marchet and P. Marijon and D. Meleshko and D. R. Mende and A. Milanese and
      N. Nagarajan and J. Nissen and S. Nurk and L. Oliker and L. Paoli and P. Peterlongo and V. C. Piro
      and J. S. Porter and S. Rasmussen and E. R. Rees and K. Reinert and B. Renard and E. M. Robertsen
      and G. L. Rosen and H.-J. Ruscheweyh and V. Sarwal and N. Segata and E. Seiler and L. Shi and F.
      Sun and S. Sunagawa and S. J. S{\o}rensen and A. Thomas and C. Tong and M. Trajkovski and J.
      Tremblay and G. Uritskiy and R. Vicedomini and Zi. Wang and Zhe. Wang and Zho. Wang and A. Warren
      and N. P. Willassen and K. Yelick and R. You and G. Zeller and Z. Zhao and S. Zhu and J. Zhu and
      R. Garrido-Oter and P. Gastmeier and S. Hacquard and S. H{\"a}u{\ss}ler and A. Khaledi and F.
      Maechler and F. Mesny and S. Radutoiu and P. Schulze-Lefert and N. Smit and T. Strowig and A.
      Bremges and A. Sczyrba and A. C. McHardy},
     booktitle = {Critical Assessment of Metagenome Interpretation - the second round of challenges},
     journal = {Nature Methods},
     month = {April},
     number = {4},
     pages = {429--440},
     publisher = {Nature Publishing Group},
     title = {Critical Assessment of Metagenome Interpretation - the second round of challenges},
     url = {http://publications.imp.fu-berlin.de/2605/},
     volume = {19},
     year = {2022}
    }
  • Jörg Winkler, Gianvito Urgese, Elisa Ficarra, Knut Reinert, “LaRA 2: parallel and vectorized program for sequence–structure alignment of RNA sequences”, vol. 23, iss. 1, 2022-01-06.
    cite this publication
    @article{fu_mi_publications2695,
     abstract = {Background The function of non-coding RNA sequences is largely determined by their
      spatial conformation, namely the secondary structure of the molecule, formed by Watson?Crick
      interactions between nucleotides. Hence, modern RNA alignment algorithms routinely take structural
      information into account. In order to discover yet unknown RNA families and infer their possible
      functions, the structural alignment of RNAs is an essential task. This task demands a lot of
      computational resources, especially for aligning many long sequences, and it therefore requires
      efficient algorithms that utilize modern hardware when available. A subset of the secondary
      structures contains overlapping interactions (called pseudoknots), which add additional complexity
      to the problem and are often ignored in available software. Results We present the SeqAn-based
      software LaRA 2 that is significantly faster than comparable software for accurate pairwise and
      multiple alignments of structured RNA sequences. In contrast to other programs our approach can
      handle arbitrary pseudoknots. As an improved re-implementation of the LaRA tool for structural
      alignments, LaRA 2 uses multi-threading and vectorization for parallel execution and a new
      heuristic for computing a lower boundary of the solution. Our algorithmic improvements yield a
      program that is up to 130 times faster than the previous version. Conclusions With LaRA 2 we
      provide a tool to analyse large sets of RNA secondary structures in relatively short time, based
      on structural alignment. The produced alignments can be used to derive structural motifs for the
      search in genomic databases.},
     author = {J{\"o}rg Winkler and Gianvito Urgese and Elisa Ficarra and Knut Reinert},
     journal = {BMC Bioinformatics},
     month = {January},
     number = {1},
     publisher = {Springer Nature},
     title = {LaRA 2: parallel and vectorized program for sequence?structure alignment of RNA
      sequences},
     url = {http://publications.imp.fu-berlin.de/2695/},
     volume = {23},
     year = {2022}
    }
  • Marius Knaust, Enrico Seiler, Knut Reinert, Thomas Steinke, “Co-Design for Energy Efficient and Fast Genomic Search: Interleaved Bloom Filter on FPGA”, 2022-02.
    cite this publication
    @inproceedings{fu_mi_publications2809,
     abstract = {Next-Generation Sequencing technologies generate a vast and exponentially increasing
      amount of sequence data. The Interleaved Bloom Filter (IBF) is a novel indexing data structure
      which is state-of-the-art for distributing approximate queries with an in-memory data structure.
      With it, a main task of sequence analysis pipelines, (approximately) searching large reference
      data sets for sequencing reads or short sequence patterns like genes, can be significantly
      accelerated. To meet performance and energy-efficiency requirements, we chose a co-design approach
      of the IBF data structure on the FPGA platform. Further, our OpenCL-based implementation allows a
      seamless integration into the widely used SeqAn C++ library for biological sequence analysis. Our
      algorithmic design and optimization strategy takes advantage of FPGA-specific features like shift
      register and the parallelization potential of many bitwise operations. We designed a well-chosen
      schema to partition data across the different memory domains on the FPGA platform using the Shared
      Virtual Memory concept. We can demonstrate significant improvements in energy efficiency of up to
      19 times and in performance of up to 5.6 times, respectively, compared to a well-tuned,
      multithreaded CPU reference.},
     author = {Marius Knaust and Enrico Seiler and Knut Reinert and Thomas Steinke},
     booktitle = {Proceedings of the 2022 ACM/SIGDA International Symposium on Field-Programmable Gate
      Arrays},
     month = {February},
     note = {conference website: https://www.isfpga.org/},
     pages = {180--189},
     title = {Co-Design for Energy Efficient and Fast Genomic Search: Interleaved Bloom Filter on FPGA},
     url = {http://publications.imp.fu-berlin.de/2809/},
     year = {2022}
    }
  • Jafar Gholami, Mohamad Reza Kamankesh, Somayeh Mohammadi, Elahe Hosseinkhani, Somayeh Abdi, “Powerful enhanced Jaya algorithm for efficiently optimizing numerical and engineering problems”, 2022-03-14.
    cite this publication
    @article{fu_mi_publications2810,
     abstract = {Over the last decade, the size and complexity of real-world problems have grown
      dramatically, necessitating more effective tools. Nature-inspired metaheuristic algorithms have
      proven to be a promising tool for solving such problems due to their performance in a variety of
      fields. JAYA algorithm is a novel population-based algorithm which could have been able to present
      reliable results. This is because it does not need any parameters to be set other than the
      population size and the maximum number of iteration. Despite its positive feedbacks, this
      algorithm should be modified to witness more efficiency. This paper aims to amend the original
      version of Jaya to present a high-efficiency version named Powerful Enhanced Jaya (PEJAYA). In
      other words, the methodology of updating position in Jaya is modified to enhance the convergence
      and search capabilities. This approach is assessed according to solve 20 well-known benchmark
      functions, feature selection, and statistical tests. The output results of proposed optimization
      algorithm are then evaluated by comparing it with other recent algorithms including crow search
      algorithm (CSA), standard version of JAYA, particle swarm optimization (PSO), dragonfly algorithm
      (DA), grasshopper optimization algorithm (GOA), moth-flame optimization (MFO) and sine?cosine
      algorithm (SCA). Solving a real-world problem is another way of checking the efficiency of this
      approach with other published works. Prompt escape from local minima, superior convergence, and
      stability demonstrate that the suggested approach is a very powerful instrument that may be
      employed in a variety of optimization situations.},
     author = {Jafar Gholami and Mohamad Reza Kamankesh and Somayeh Mohammadi and Elahe Hosseinkhani and
      Somayeh Abdi},
     journal = {Soft Computing},
     month = {March},
     title = {Powerful enhanced Jaya algorithm for efficiently optimizing numerical and engineering
      problems},
     url = {http://publications.imp.fu-berlin.de/2810/},
     year = {2022}
    }
  • Mitra Darvish, Enrico Seiler, Svenja Mehringer, RenĂ© Rahn, Knut Reinert, Yann Ponty, “Needle: a fast and space-efficient prefilter for estimating the quantification of very large collections of expression experiments”, vol. 38, iss. 17, 2022-07-08.
    cite this publication
    @article{fu_mi_publications2845,
     abstract = {Motivation The ever-growing size of sequencing data is a major bottleneck in
      bioinformatics as the advances of hardware development cannot keep up with the data growth.
      Therefore, an enormous amount of data is collected but rarely ever reused, because it is nearly
      impossible to find meaningful experiments in the stream of raw data. Results As a solution, we
      propose Needle, a fast and space-efficient index which can be built for thousands of experiments
      in {\ensuremath{<}}2 h and can estimate the quantification of a transcript in these experiments in
      seconds, thereby outperforming its competitors. The basic idea of the Needle index is to create
      multiple interleaved Bloom filters that each store a set of representative k-mers depending on
      their multiplicity in the raw data. This is then used to quantify the query. Availability and
      implementation https://github.com/seqan/needle.},
     author = {Mitra Darvish and Enrico Seiler and Svenja Mehringer and Ren{\'e} Rahn and Knut Reinert
      and Yann Ponty},
     journal = {Bioinformatics},
     month = {July},
     number = {17},
     pages = {4100--4108},
     title = {Needle: a fast and space-efficient prefilter for estimating the quantification of very
      large collections of expression experiments},
     url = {http://publications.imp.fu-berlin.de/2845/},
     volume = {38},
     year = {2022}
    }
  • Thomas Krannich, “Contributions to the detection of non-reference sequences in population-scale NGS data”, 2022-06-02.
    cite this publication
    @phdthesis{fu_mi_publications2854,
     abstract = {Non-reference sequence (NRS) variants are a less frequently investigated class of
      genomic structural variants (SV). Here, DNA sequences are found within an individual that are
      novel with respect to a given reference. NRS occur predominantly due to the fact that a linear
      reference genome lacks biological diversity and ancestral sequence if it was primarily derived
      from a single or few individuals. Therefore, newly sequenced individuals can yield genomic
      sequences which are absent from a reference genome. With the increasing throughput of sequencing
      technologies, SV detection has become possible across tens of thousands of individuals. When using
      short-read data, the detection of NRS variants inevitably involves a de novo assembly which is a
      complex computational problem and requires high-quality sequence data at high coverage. Previous
      studies have demonstrated how sequence data of multiple genomes can be combined for the reliable
      detection of NRS variants. However, the algorithms proposed in these studies have a limited
      capability to process large sets of genomes. This thesis introduces novel contributions for the
      discovery of NRS variants in many genomes, which scale to considerably larger numbers of genomes
      than previous methods. A practical software tool, PopIns2, that was developed to apply the
      presented methods is elucidated in greater detail. The highlight among the new contributions is a
      procedure to merge contig assemblies of unaligned reads from many individuals into a single set of
      NRS by heuristically generating a weighted minimum path cover for a colored de Bruijn graph. Tests
      on simulated data show that PopIns2 ranks among the best approaches in terms of quality and
      reliability and that its approach yields the best precision for a growing number of genomes
      processed. Results on the Polaris Diversity Cohort and a set of 1000 Icelandic human genomes
      demonstrate unmatched scalability for the application on population-scale datasets.},
     author = {Thomas Krannich},
     month = {June},
     school = {Freie Universit{\"a}t Berlin},
     title = {Contributions to the detection of non-reference sequences in population-scale NGS data},
     url = {http://publications.imp.fu-berlin.de/2854/},
     year = {2022}
    }
  • Sebastian Niehus, “Multi-Sample Approaches and Applications for Structural Variant Detection”, 2022-07-28.
    cite this publication
    @phdthesis{fu_mi_publications2855,
     abstract = {In recent years, advances in the field of sequencing technologies have enabled the
      field of population-scale sequencing studies. These studies aim to sequence and analyze a large
      set of individuals from one or multiple populations, with the aim of gaining insight into
      underlying genetic structure, similarities and differences. Collections of genetic variation and
      possible connections to various disease are some of the products of this area of research. The
      potential of population studies is widely considered to be huge and many more endeavors of this
      kind are expected in the near future. This opportunity comes with a big challenge because many
      computational tools that are used for the analysis of sequencing data were not designed for
      cohorts of this size and may suffer from limited scalability. It is therefore vital that the
      computational tools required for the analysis of population-scale data keep up with the quickly
      growing amounts of data. This thesis contributes to the field of population-scale genetics in the
      development and application of a novel approach for structural variant detection. It has
      explicitly been designed with the large amounts of population-scale sequencing data in mind. The
      presented approach is capable of analyzing tens of thousands of whole-genome short-read sequencing
      samples jointly. This joint analysis is driven by a tailored joint likelihood ratio model that
      integrates information from many genomes. The efficient approach does not only save computational
      resources but also allows to combine the data across all samples to make sensitive and specific
      predictions about the presence and genotypes of structural variation present within the analyzed
      population. This thesis demonstrates that this approach and the computational tool PopDel that
      implements it compare favorably to current state-of-the-art structural variant callers that have
      been used in previous population-scale studies. Extensive benchmarks on simulated and real world
      sequencing data are provided to show the performance of the presented approach. Further, a first
      finding of medical relevance that directly stems from the application of PopDel on the genomes of
      almost 50,000 Icelanders is presented. This thesis therefore provides a novel tool and new ideas
      to further push the boundaries of the analysis of massive amounts of next generation sequencing
      data and to deepen our understanding of structural variation and their implications for human
      health.},
     author = {Sebastian Niehus},
     month = {July},
     school = {Freie Universit{\"a}t Berlin},
     title = {Multi-Sample Approaches and Applications for Structural Variant Detection},
     url = {http://publications.imp.fu-berlin.de/2855/},
     year = {2022}
    }
  • Marie Hoffmann, “What is in my Sample? Challenges and Approaches for Unveiling the Hidden Diversity in Plankton Samples”, 2022.
    cite this publication
    @phdthesis{fu_mi_publications3253,
     abstract = {The goal of this work is to deploy a primer search tool (PriSeT) suitable for
      taxonomically broad, sparse, and uncurated datasets of reference sequences. I discuss the
      theoretical and practical challenges when sequence datasets are large. Uncurated online reference
      databases are often the only source available when designing new primer sequences, studying the
      effectiveness, and for species identification. As a case study, two different identification
      methods for planktonic microorganisms from freshwater samples are presented: identification via
      light microscopy and DNA sequencing. The sequencing approach will replace the manual method to a
      large extent, but still needs to be improved and requires many costly trial-and-error iterations.
      The robust primer search tool PriSeT is here developed and designed to shorten the optimization
      time and to facilitate new types of in silico analyses. I evaluate PriSeT on 18S rRNA genes from
      all major plankton clades and on whole RNA genomes. The resulting primer sequences are compared to
      published primer pairs. Finally, the workflow of an academic research group planning and
      conducting metabarcoding experiments is critically reviewed. I present a database schema designed
      to summarize key information and enable researchers to be more productive in less time. The scheme
      also alleviates new types of meta-analysis that are not possible when data are scattered, such as
      quantitative and qualitative comparisons between different studies.},
     author = {Marie Hoffmann},
     school = {Freie Universit{\"a}t Berlin},
     title = {What is in my Sample? Challenges and Approaches for Unveiling the Hidden Diversity in
      Plankton Samples},
     url = {http://publications.imp.fu-berlin.de/3253/},
     year = {2022}
    }

2021

  • Silver A Wolf, Lennard Epping, Sandro Andreotti, Knut Reinert, Torsten Semmler, Inanc Birol, “SCORE: Smart Consensus Of RNA Expression—a consensus tool for detecting differentially expressed genes in bacteria”, vol. 37, iss. 3, 2021-02-01.
    cite this publication
    @article{fu_mi_publications2513,
     abstract = {RNA-sequencing (RNA-Seq) is the current method of choice for studying bacterial
      transcriptomes. To date, many computational pipelines have been developed to predict
      differentially expressed genes from RNA-Seq data, but no gold-standard has been widely accepted.
      We present the Snakemake-based tool Smart Consensus Of RNA Expression (SCORE) which uses a
      consensus approach founded on a selection of well-established tools for differential gene
      expression analysis. This allows SCORE to increase the overall prediction accuracy and to merge
      varying results into a single, human-readable output. SCORE performs all steps for the analysis of
      bacterial RNA-Seq data, from read preprocessing to the overrepresentation analysis of
      significantly associated ontologies. Development of consensus approaches like SCORE will help to
      streamline future RNA-Seq workflows and will fundamentally contribute to the creation of new
      gold-standards for the analysis of these types of data. Availability and implementation:
      https://github.com/SiWolf/SCORE.},
     author = {Silver A Wolf and Lennard Epping and Sandro Andreotti and Knut Reinert and Torsten
      Semmler and Inanc Birol},
     journal = {Bioinformatics},
     month = {February},
     number = {3},
     pages = {426--428},
     publisher = {Oxford University Press, Oxford Academic},
     title = {SCORE: Smart Consensus Of RNA Expression{--}a consensus tool for detecting differentially
      expressed genes in bacteria},
     url = {http://publications.imp.fu-berlin.de/2513/},
     volume = {37},
     year = {2021}
    }
  • Enrico Seiler, Svenja Mehringer, Mitra Darvish, Etienne Turc, Knut Reinert, “Raptor: A fast and space-efficient pre-filter for querying very large collections of nucleotide sequences”, vol. 24, iss. 7, 2021-07-23.
    cite this publication
    @article{fu_mi_publications2519,
     abstract = {We present Raptor, a tool for approximately searching many queries in large collections
      of nucleotide sequences. In comparison with similar tools like Mantis and COBS, Raptor is 12-144
      times faster and uses up to 30 times less memory. Raptor uses winnowing minimizers to define a set
      of representative k-mers, an extension of the Interleaved Bloom Filters (IBF) as a set membership
      data structure, and probabilistic thresholding for minimizers. Our approach allows compression and
      a partitioning of the IBF to enable the effective use of secondary memory. Competing Interest
      Statement: The authors have declared no competing interest.},
     author = {Enrico Seiler and Svenja Mehringer and Mitra Darvish and Etienne Turc and Knut Reinert},
     booktitle = {Raptor: A fast and space-efficient pre-filter for querying very large collections of
      nucleotide sequences},
     journal = {iScience},
     month = {July},
     number = {7},
     pages = {102782},
     publisher = {Elsevier},
     title = {Raptor: A fast and space-efficient pre-filter for querying very large collections of
      nucleotide sequences},
     url = {http://publications.imp.fu-berlin.de/2519/},
     volume = {24},
     year = {2021}
    }
  • Marie Hoffmann, Michael T. Monaghan, Knut Reinert, “PriSeT: Efficient De Novo Primer Discovery”, 2021-08-01.
    cite this publication
    @article{fu_mi_publications2520,
     abstract = {Motivation: DNA metabarcoding is a commonly applied technique used to infer the species
      composition of environmental samples. These samples can comprise hundreds of organisms that can be
      closely or very distantly related in the taxonomic tree of life. DNA metabarcoding combines
      polymerase chain reaction (PCR) and next-generation sequencing (NGS), whereby a short, homologous
      sequence of DNA is amplified and sequenced from all members of the community. Sequences are then
      taxonomically identified based on their match to a reference database. Ideally, each species of
      interest would have a unique DNA barcode. This short, variable sequence needs to be flanked by
      relatively conserved regions that can be used as primer binding sites. Appropriate PCR primer
      pairs would match to a broad evolutionary range of taxa, such that we only need a few to achieve
      high taxonomic coverage. At the same time however, the DNA barcodes between primer pairs should be
      different to allow us to distinguish between species to improve resolution. This poses an
      interesting optimization problem. More specifically: Given a set of references ? = \{R1, R2, ?,
      Rm\}, the problem is to find a primer set P balancing both: high taxonomic coverage and high
      resolution. This goal can be captured by filtering for frequent primers and ranking by coverage or
      variation, i.e. the number of unique barcodes. Here we present the software PriSeT, an offline
      primer discovery tool that is capable of processing large libraries and is robust against
      mislabeled or low quality references. It tackles the computationally expensive steps with linear
      runtime filters and efficient encodings. Results: We first evaluated PriSeT on references (mostly
      18S rRNA genes) from 19 clades covering eukaryotic organisms that are typical for freshwater
      plankton samples. PriSeT recovered several published primer sets as well as additional, more
      chemically suitable primer sets. For these new sets, we compared frequency, taxon coverage, and
      amplicon variation with published primer sets. For 11 clades we found de novo primer pairs that
      cover more taxa than the published ones, and for six clades de novo primers resulted in greater
      sequence (i.e., DNA barcode) variation. We also applied PriSeT to 19 SARS-CoV-2 genomes and
      computed 114 new primer pairs with the additional constraint that the sequences have no
      co-occurrences in other taxa. These primer sets would be suitable for empirical testing.
      Availability: https://github.com/mariehoffmann/PriSeT},
     author = {Marie Hoffmann and Michael T. Monaghan and Knut Reinert},
     booktitle = {PriSeT: Efficient De Novo Primer Discovery},
     journal = {Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and
      Health Informatics},
     month = {August},
     pages = {1--12},
     publisher = {ACM},
     title = {PriSeT: Efficient De Novo Primer Discovery},
     url = {http://publications.imp.fu-berlin.de/2520/},
     year = {2021}
    }
  • Sandeep Keshavan, Fernando Torres AndĂłn, Audrey Gallud, Wei Chen, Knut Reinert, Lang Tran, Bengt Fadeel, “Profiling of Sub-Lethal in Vitro Effects of Multi-Walled Carbon Nanotubes Reveals Changes in Chemokines and Chemokine Receptors”, vol. 11, iss. 4, 2021-03-30.
    cite this publication
    @article{fu_mi_publications2575,
     abstract = {Engineered nanomaterials are potentially very useful for a variety of applications, but
      studies are needed to ascertain whether these materials pose a risk to human health. Here, we
      studied three benchmark nanomaterials (Ag nanoparticles, TiO2 nanoparticles, and multi-walled
      carbon nanotubes, MWCNTs) procured from the nanomaterial repository at the Joint Research Centre
      of the European Commission. Having established a sub-lethal concentration of these materials using
      two human cell lines representative of the immune system and the lungs, respectively, we performed
      RNA sequencing of the macrophage-like cell line after exposure for 6, 12, and 24 h. Downstream
      analysis of the transcriptomics data revealed significant effects on chemokine signaling pathways.
      CCR2 was identified as the most significantly upregulated gene in MWCNT-exposed cells. Using
      multiplex assays to evaluate cytokine and chemokine secretion, we could show significant effects
      of MWCNTs on several chemokines, including CCL2, a ligand of CCR2. The results demonstrate the
      importance of evaluating sub-lethal concentrations of nanomaterials in relevant target cells.},
     author = {Sandeep Keshavan and Fernando Torres And{\'o}n and Audrey Gallud and Wei Chen and Knut
      Reinert and Lang Tran and Bengt Fadeel},
     journal = {Nanomaterials},
     keywords = {multi-walled carbon nanotubes; nanoparticles; chemokines; macrophages;
      transcriptomics},
     month = {March},
     number = {4},
     pages = {883},
     publisher = {MDPI},
     title = {Profiling of Sub-Lethal in Vitro Effects of Multi-Walled Carbon Nanotubes Reveals Changes
      in Chemokines and Chemokine Receptors},
     url = {http://publications.imp.fu-berlin.de/2575/},
     volume = {11},
     year = {2021}
    }
  • Kerstin Neubert, Eric Zuchantke, Robert Maximilian Leidenfrost, Röbbe WĂŒnschiers, Josephine GrĂŒtzke, Burkhard Malorny, Holger Brendebach, Sascha Al Dahouk, Timo Homeier, Helmut Hotzel, Knut Reinert, Herbert Tomaso, Anne Busch, “Testing assembly strategies of Francisella tularensis genomes to infer an evolutionary conservation analysis of genomic structures”, vol. 22, iss. 1, 2021-11-14.
    cite this publication
    @article{fu_mi_publications2696,
     abstract = {Background We benchmarked sequencing technology and assembly strategies for short-read,
      long-read, and hybrid assemblers in respect to correctness, contiguity, and completeness of
      assemblies in genomes of Francisella tularensis. Benchmarking allowed in-depth analyses of genomic
      structures of the Francisella pathogenicity islands and insertion sequences. Five major
      high-throughput sequencing technologies were applied, including next-generation ?short-read? and
      third-generation ?long-read? sequencing methods. Results We focused on short-read assemblers,
      hybrid assemblers, and analysis of the genomic structure with particular emphasis on insertion
      sequences and the Francisella pathogenicity island. The A5-miseq pipeline performed best for MiSeq
      data, Mira for Ion Torrent data, and ABySS for HiSeq data from eight short-read assembly methods.
      Two approaches were applied to benchmark long-read and hybrid assembly strategies: long-read-first
      assembly followed by correction with short reads (Canu/Pilon, Flye/Pilon) and short-read-first
      assembly along with scaffolding based on long reads (Unicyler, SPAdes). Hybrid assembly can
      resolve large repetitive regions best with a ?long-read first? approach. Conclusions Genomic
      structures of the Francisella pathogenicity islands frequently showed misassembly. Insertion
      sequences (IS) could be used to perform an evolutionary conservation analysis. A phylogenetic
      structure of insertion sequences and the evolution within the clades elucidated the clade
      structure of the highly conservative F. tularensis.},
     author = {Kerstin Neubert and Eric Zuchantke and Robert Maximilian Leidenfrost and R{\"o}bbe
      W{\"u}nschiers and Josephine Gr{\"u}tzke and Burkhard Malorny and Holger Brendebach and Sascha Al
      Dahouk and Timo Homeier and Helmut Hotzel and Knut Reinert and Herbert Tomaso and Anne Busch},
     journal = {BMC Genomics},
     month = {November},
     number = {1},
     pages = {822},
     publisher = {Springer Nature},
     title = {Testing assembly strategies of Francisella tularensis genomes to infer an evolutionary
      conservation analysis of genomic structures},
     url = {http://publications.imp.fu-berlin.de/2696/},
     volume = {22},
     year = {2021}
    }
  • Ulf Leser, Marcus Hilbrich, Claudia Draxl, Peter Eisert, Lars Grunske, Patrick Hostert, Dagmar KainmĂŒller, Odej Kao, Birte Kehr, Timo Kehrer, Christoph Koch, Volker Markl, Henning Meyerhenke, Tilmann Rabl, Alexander Reinefeld, Knut Reinert, Kerstin Ritter, Björn Scheuermann, Florian Schintke, Nicole Schweikardt, Matthias Weidlich, “The Collaborative Research Center FONDA”, vol. 21, iss. 3, 2021-11-12.
    cite this publication
    @article{fu_mi_publications2697,
     abstract = {Today?s scientific data analysis very often requires complex Data Analysis Workflows
      (DAWs) executed over distributed computational infrastructures, e.g., clusters. Much research
      effort is devoted to the tuning and performance optimization of specific workflows for specific
      clusters. However, an arguably even more important problem for accelerating research is the
      reduction of development, adaptation, and maintenance times of DAWs. We describe the design and
      setup of the Collaborative Research Center (CRC) 1404 ?FONDA -? Foundations of Workflows for
      Large-Scale Scientific Data Analysis?, in which roughly 50 researchers jointly investigate new
      technologies, algorithms, and models to increase the portability, adaptability, and dependability
      of DAWs executed over distributed infrastructures. We describe the motivation behind our project,
      explain its underlying core concepts, introduce FONDA?s internal structure, and sketch our vision
      for the future of workflow-based scientific data analysis. We also describe some lessons learned
      during the ?making of? a CRC in Computer Science with strong interdisciplinary components, with
      the aim to foster similar endeavors.},
     author = {Ulf Leser and Marcus Hilbrich and Claudia Draxl and Peter Eisert and Lars Grunske and
      Patrick Hostert and Dagmar Kainm{\"u}ller and Odej Kao and Birte Kehr and Timo Kehrer and
      Christoph Koch and Volker Markl and Henning Meyerhenke and Tilmann Rabl and Alexander Reinefeld
      and Knut Reinert and Kerstin Ritter and Bj{\"o}rn Scheuermann and Florian Schintke and Nicole
      Schweikardt and Matthias Weidlich},
     journal = {Datenbank-Spektrum},
     month = {November},
     number = {3},
     pages = {255--260},
     publisher = {Springer Nature},
     title = {The Collaborative Research Center FONDA},
     url = {http://publications.imp.fu-berlin.de/2697/},
     volume = {21},
     year = {2021}
    }
  • Sara Hetzel, Pay Giesselmann, Knut Reinert, Alexander Meissner, Helene Kretzmer, Can Alkan, “RLM: fast and simplified extraction of read-level methylation metrics from bisulfite sequencing data”, vol. 37, iss. 21, 2021-11-01.
    cite this publication
    @article{fu_mi_publications2698,
     abstract = {Bisulfite sequencing data provide value beyond the straightforward methylation
      assessment by analyzing single-read patterns. Over the past years, various metrics have been
      established to explore this layer of information. However, limited compatibility with alignment
      tools, reference genomes or the measurements they provide present a bottleneck for most groups to
      routinely perform read-level analysis. To address this, we developed RLM, a fast and scalable tool
      for the computation of several frequently used read-level methylation statistics. RLM supports
      standard alignment tools, works independently of the reference genome and handles most sequencing
      experiment designs. RLM can process large input files with a billion reads in just a few hours on
      common workstations. Availability and implementation: https://github.com/sarahet/RLM},
     author = {Sara Hetzel and Pay Giesselmann and Knut Reinert and Alexander Meissner and Helene
      Kretzmer and Can Alkan},
     journal = {Bioinformatics},
     month = {November},
     number = {21},
     pages = {3934--3935},
     publisher = {Oxford Univ. Press},
     title = {RLM: fast and simplified extraction of read-level methylation metrics from bisulfite
      sequencing data},
     url = {http://publications.imp.fu-berlin.de/2698/},
     volume = {37},
     year = {2021}
    }
  • Hannes Peer Hauswedell, “SeqAn3 – Sequence Analysis and Modern C++”, 2021-05-28.
    cite this publication
    @phdthesis{fu_mi_publications2850,
     abstract = {This thesis introduces SeqAn3, a new software library built with Modern C++ to solve
      problems from the domain of sequence analysis in bioinformatics. It discusses previous versions of
      the library in detail and explains the importance of highly performing programming languages like
      C++. Complexity in the design of the library and of the programming language itself are identified
      as the major obstacles to user satisfaction, widespread adoption and long-term viability of the
      project. Therefore, based on very fundamental changes in the C++ programming language, a new
      library design is formulated and implemented. Its impact is showcased by porting the local aligner
      called Lambda from SeqAn2 to SeqAn3. Both, the library and the application are highly relevant in
      practice and prove that simpler and more compact solutions are possible. This thesis documents the
      process of creating said software, contributing vital information to the fields of research
      software engineering, library design and to a certain degree also applied programming language
      research. As one of the first larger projects to be designed fully around C++20 features, it has
      instructive value beyond bioinformatics.},
     author = {Hannes Peer Hauswedell},
     month = {May},
     school = {Freie Universit{\"a}t Berlin},
     title = {SeqAn3 ? Sequence Analysis and Modern C++},
     url = {http://publications.imp.fu-berlin.de/2850/},
     year = {2021}
    }
  • Pay Giesselmann, “Genome Analysis Methods using Long Read Nanopore Sequencing”, 2021-12-15.
    cite this publication
    @phdthesis{fu_mi_publications2852,
     abstract = {Third-generation long-read technologies denote the latest progression in high
      throughput DNA and RNA sequence analysis. Complementing the widespread second-generation
      short-read platforms, long-read sequencing adds unique application opportunities by generating
      previously unattainable read lengths. Despite the remaining higher error rate compared to short
      reads, single-molecule real-time sequencing (SMRT) and nanopore sequencing advanced to be
      state-of-the-art for {$\backslash$}textit\{de-novo\} genome assemblies and identification of
      structural variants. Continuous throughput and accuracy improvements lead to development of novel
      methods and applications at a fast pace. We identify major application fields and key
      bioinformatic software for long-read sequencing data analysis by employing a data driven
      literature research. The integration of citations and keywords into a literature graph provides a
      scaling approach to analyze an exponentially growing number of third-generation sequencing related
      publications. Even though sparking the development of countless bioinformatics software, the
      streamlined nanopore data processing into standardized formats is still lacking. As an enabling
      step for its successful application, we developed {$\backslash$}textit\{Nanopype\}, a modular and
      scalable pipeline. Our approach facilitates the basic steps of basecalling, alignment,
      methylation- and structural variant detection with exchangeable tools in each module. Optimized
      for the usage on high performance compute clusters, we propose a raw data management, capable of
      handling multiple sequencing devices placed locally and remotely. Strict version control of
      integrated tools and deployment as containerized software, ensure reproducibility across projects
      and laboratories. Finally, we analyze disease associated repeat regions utilizing targeted
      nanopore sequencing and the {$\backslash$}textit\{Nanopype\} processing infrastructure. The
      expansion of unstable genomic short tandem repeats (STRs) is of particular interest as it causes
      more than 30 Mendelian human disorders. Long stretches of repetitive sequence render these regions
      inaccessible for short-read sequencing by synthesis. Furthermore, finding current nanopore
      basecalling algorithms insufficient to resolve the repeat length, we developed
      {$\backslash$}textit\{STRique\}, a raw nanopore signal based repeat detection and quantification
      software. We demonstrate the precise analysis of repeat lengths on patient-derived samples
      containing C9orf72 and FMR1 repeat expansions. The additional integration of repeat- and nearby
      promoter-methylation levels reveal a repeat length depending gain, suggesting an epigenetic
      response to the expansion. Taken together, this work contributes to further increase the usability
      and provides novel insights based on third-generation nanopore sequencing.},
     author = {Pay Giesselmann},
     month = {December},
     school = {Freie Universit{\"a}t Berlin},
     title = {Genome Analysis Methods using Long Read Nanopore Sequencing},
     url = {http://publications.imp.fu-berlin.de/2852/},
     year = {2021}
    }

2020

  • Julianus Pfeuffer, Timo Sachsenberg, Tjeerd M. H. Dijkstra, Oliver Serang, Knut Reinert, Oliver Kohlbacher, “EPIFANY: A Method for Efficient High-Confidence Protein Inference”, vol. 19, iss. 3, 2020-01-24.
    cite this publication
    @article{fu_mi_publications2429,
     abstract = {Accurate protein inference in the presence of shared peptides is still one of the key
      problems in bottom-up proteomics. Most protein inference tools employing simple heuristic
      inference strategies are efficient but exhibit reduced accuracy. More advanced probabilistic
      methods often exhibit better inference quality but tend to be too slow for large data sets. Here,
      we present a novel protein inference method, EPIFANY, combining a loopy belief propagation
      algorithm with convolution trees for efficient processing of Bayesian networks. We demonstrate
      that EPIFANY combines the reliable protein inference of Bayesian methods with significantly
      shorter runtimes. On the 2016 iPRG protein inference benchmark data, EPIFANY is the only tested
      method that finds all true-positive proteins at a 5\% protein false discovery rate (FDR) without
      strict prefiltering on the peptide-spectrum match (PSM) level, yielding an increase in
      identification performance (+10\% in the number of true positives and +14\% in partial AUC)
      compared to previous approaches. Even very large data sets with hundreds of thousands of spectra
      (which are intractable with other Bayesian and some non-Bayesian tools) can be processed with
      EPIFANY within minutes. The increased inference quality including shared peptides results in
      better protein inference results and thus increased robustness of the biological hypotheses
      generated. EPIFANY is available as open-source software for all major platforms at
      https://OpenMS.de/epifany.},
     author = {Julianus Pfeuffer and Timo Sachsenberg and Tjeerd M. H. Dijkstra and Oliver Serang and
      Knut Reinert and Oliver Kohlbacher},
     journal = {Journal of Proteome Research},
     keywords = {bottom-up proteomics, protein inference, Bayesian networks, convolution trees, loopy
      belief propagation, iPRG2016},
     month = {January},
     number = {3},
     pages = {1060--1072},
     publisher = {ACS Publications},
     title = {EPIFANY: A Method for Efficient High-Confidence Protein Inference},
     url = {http://publications.imp.fu-berlin.de/2429/},
     volume = {19},
     year = {2020}
    }
  • Christopher Schiefer, Marc Bux, Joergen Brandt, Clemens Messerschmidt, Knut Reinert, Dieter Beule, Ulf Leser, “Portability of Scientific Workflows in NGS Data Analysis: A Case Study”, 2020-06-04.
    cite this publication
    @techreport{fu_mi_publications2510,
     abstract = {The analysis of next-generation sequencing (NGS) data requires complex computational
      workflows consisting of dozens of autonomously developed yet interdependent processing steps.
      Whenever large amounts of data need to be processed, these workflows must be executed on a
      parallel and/or distributed systems to ensure reasonable runtime. Porting a workflow developed for
      a particular system on a particular hardware infrastructure to another system or to another
      infrastructure is non-trivial, which poses a major impediment to the scientific necessities of
      workflow reproducibility and workflow reusability. In this work, we describe our efforts to port a
      state-of-the-art workflow for the detection of specific variants in whole-exome sequencing of
      mice. The workflow originally was developed in the scientific workflow system snakemake for
      execution on a high-performance cluster controlled by Sun Grid Engine. In the project, we ported
      it to the scientific workflow system SaasFee that can execute workflows on (multi-core)
      stand-alone servers or on clusters of arbitrary sizes using the Hadoop. The purpose of this port
      was that also owners of low-cost hardware infrastructures, for which Hadoop was made for, become
      able to use the workflow. Although both the source and the target system are called scientific
      workflow systems, they differ in numerous aspects, ranging from the workflow languages to the
      scheduling mechanisms and the file access interfaces. These differences resulted in various
      problems, some expected and more unexpected, that had to be resolved before the workflow could be
      run with equal semantics. As a side-effect, we also report cost/runtime ratios for a
      state-of-the-art NGS workflow on very different hardware platforms: A comparably cheap stand-alone
      server (80 threads), a mid-cost, mid-sized cluster (552 threads), and a high-end HPC system (3784
      threads).},
     author = {Christopher Schiefer and Marc Bux and Joergen Brandt and Clemens Messerschmidt and Knut
      Reinert and Dieter Beule and Ulf Leser},
     month = {June},
     publisher = {arXiv.org},
     title = {Portability of Scientific Workflows in NGS Data Analysis: A Case Study},
     type = {Other},
     url = {http://publications.imp.fu-berlin.de/2510/},
     year = {2020}
    }
  • J.J. Kim, J. Kim, K. Reinert, “Vaquita-LR: A new bioinformatics tool for identifying structural variants using long and short reads. In: Abstracts from the 53rd European Society of Human Genetics (ESHG) Conference: Interactive e-Posters”, vol. 28, iss. S1, 2020-12-01.
    cite this publication
    @inproceedings{fu_mi_publications2511,
     abstract = {Introduction: The identification of structural variation in the genome is difficult due
      to the lack of a ?perfect? sequencing technology. By combining short and long read sequencing
      data, Vaquita-LR is a novel bioinformatics approach to identify more variants with higher accuracy
      by utilizing the strengths of one method to overcome the weaknesses of the other. Materials and
      Methods: Vaquita-LR is an extension of Vaquita, a short read variant caller, which has been
      modified to identify potential variants in long reads in addition to short reads and merge them to
      provide a final set of variants. Vaquita-LR takes into consideration the read depth, read length,
      and other characteristics of the sequencing data to add weight to more confident calls.
      Additionally, it adapts techniques from Pilon to improve the accuracy of the long read data using
      relevant short read information. Results: By combining short and long reads, Vaquita-LR is able to
      outperform other structural variant callers, including meta callers which combine results from
      other callers. Importantly, supplying long reads is effective at sequencing depths as shallow as
      1x. Using this combination allows Vaquita-LR to better filter out false positives while retaining
      true positives, providing a better list of possible causal variants for further investigation.
      Conclusions: With the abundance of data available today, it is important to consider how the data
      can be effectively merged to better serve our needs. Vaquita-LR is an initial step in showing the
      usefulness of integrating different sequencing data types when identifying structural variants.},
     author = {J.J. Kim and J. Kim and K. Reinert},
     booktitle = {53rd European Society of Human Genetics (ESHG) Conference},
     journal = {European Journal of Human Genetics},
     month = {December},
     number = {S1},
     pages = {141--797},
     title = {Vaquita-LR: A new bioinformatics tool for identifying structural variants using long and
      short reads. In: Abstracts from the 53rd European Society of Human Genetics (ESHG) Conference:
      Interactive e-Posters},
     url = {http://publications.imp.fu-berlin.de/2511/},
     volume = {28},
     year = {2020}
    }
  • Robert Pieper, Temesgen H. Dadi, Laura Pieper, Wilfried Vahjen, AndrĂ© Franke, Knut Reinert, JĂŒrgen Zentek, “Concentration and chemical form of dietary zinc shape the porcine colon microbiome, its functional capacity and antibiotic resistance gene repertoire”, vol. 14, iss. 11, 2020-08-03.
    cite this publication
    @article{fu_mi_publications2512,
     abstract = {Despite a well-documented effect of high dietary zinc oxide on the pig intestinal
      microbiota composition less is it yet known about changes in microbial functional properties or
      the effect of organic zinc sources. Forty weaning piglets in four groups were fed diets
      supplemented with 40 or 110 ppm zinc as zinc oxide, 110 ppm as Zn-Lysinate, or 2500 ppm as zinc
      oxide. Host zinc homeostasis, intestinal zinc fractions, and ileal nutrient digestibility were
      determined as main nutritional and physiological factors putatively driving colon microbial
      ecology. Metagenomic sequencing of colon microbiota revealed only clear differences at genus level
      for the group receiving 2500 ppm zinc oxide. However, a clear group differentiation according to
      dietary zinc concentration and source was observed at species level. Functional analysis revealed
      significant differences in genes related to stress response, mineral, and carbohydrate metabolism.
      Taxonomic and functional gene differences were accompanied with clear effects in microbial
      metabolite concentration. Finally, a selection of certain antibiotic resistance genes by dietary
      zinc was observed. This study sheds further light onto the consequences of concentration and
      chemical form of dietary zinc on microbial ecology measures and the resistome in the porcine
      colon.},
     author = {Robert Pieper and Temesgen H. Dadi and Laura Pieper and Wilfried Vahjen and Andr{\'e}
      Franke and Knut Reinert and J{\"u}rgen Zentek},
     journal = {The ISME Journal},
     month = {August},
     number = {11},
     pages = {2783--2793},
     publisher = {Nature Portfolio},
     title = {Concentration and chemical form of dietary zinc shape the porcine colon microbiome, its
      functional capacity and antibiotic resistance gene repertoire},
     url = {http://publications.imp.fu-berlin.de/2512/},
     volume = {14},
     year = {2020}
    }
  • Bernhard Y Renard, Knut Reinert, Enrico Seiler, Temesgen H Dadi, Vitor C Piro, “ganon: precise metagenomics classification against large and up-to-date sets of reference sequences”, vol. 36, iss. Supple, 2020-07-13.
    cite this publication
    @article{fu_mi_publications2514,
     abstract = {Motivation: The exponential growth of assembled genome sequences greatly benefits
      metagenomics studies. However, currently available methods struggle to manage the increasing
      amount of sequences and their frequent updates. Indexing the current RefSeq can take days and
      hundreds of GB of memory on large servers. Few methods address these issues thus far, and even
      though many can theoretically handle large amounts of references, time/memory requirements are
      prohibitive in practice. As a result, many studies that require sequence classification use often
      outdated and almost never truly up-to-date indices. Results: Motivated by those limitations, we
      created ganon, a k-mer-based read classification tool that uses Interleaved Bloom Filters in
      conjunction with a taxonomic clustering and a k-mer counting/filtering scheme. Ganon provides an
      efficient method for indexing references, keeping them updated. It requires {\ensuremath{<}}55 min
      to index the complete RefSeq of bacteria, archaea, fungi and viruses. The tool can further keep
      these indices up-to-date in a fraction of the time necessary to create them. Ganon makes it
      possible to query against very large reference sets and therefore it classifies significantly more
      reads and identifies more species than similar methods. When classifying a high-complexity CAMI
      challenge dataset against complete genomes from RefSeq, ganon shows strongly increased precision
      with equal or better sensitivity compared with state-of-the-art tools. With the same dataset
      against the complete RefSeq, ganon improved the F1-score by 65\% at the genus level. It supports
      taxonomy- and assembly-level classification, multiple indices and hierarchical classification.
      Availability and implementation: The software is open-source and available at:
      https://gitlab.com/rki\_bioinformatics/ganon.},
     author = {Bernhard Y Renard and Knut Reinert and Enrico Seiler and Temesgen H Dadi and Vitor C
      Piro},
     journal = {Bioinformatics},
     month = {July},
     number = {Supple},
     pages = {i12--i20},
     publisher = {Oxford University Press, Oxford Academic},
     title = {ganon: precise metagenomics classification against large and up-to-date sets of reference
      sequences},
     url = {http://publications.imp.fu-berlin.de/2514/},
     volume = {36},
     year = {2020}
    }
  • Knut Reinert, Costas S Iliopoulos, Mai Alzamel, Christopher Pockrandt, Jinbo Xu, “GenMap: ultra-fast computation of genome mappability”, vol. 36, iss. 12, 2020-04-04.
    cite this publication
    @article{fu_mi_publications2515,
     abstract = {Motivation: Computing the uniqueness of k-mers for each position of a genome while
      allowing for up to e mismatches is computationally challenging. However, it is crucial for many
      biological applications such as the design of guide RNA for CRISPR experiments. More formally, the
      uniqueness or (k, e)-mappability can be described for every position as the reciprocal value of
      how often this k-mer occurs approximately in the genome, i.e. with up to e mismatches. Results: We
      present a fast method GenMap to compute the (k, e)-mappability. We extend the mappability
      algorithm, such that it can also be computed across multiple genomes where a k-mer occurrence is
      only counted once per genome. This allows for the computation of marker sequences or finding
      candidates for probe design by identifying approximate k-mers that are unique to a genome or that
      are present in all genomes. GenMap supports different formats such as binary output, wig and bed
      files as well as csv files to export the location of all approximate k-mers for each genomic
      position. Availability and implementation: GenMap can be installed via bioconda. Binaries and C++
      source code are available on https://github.com/cpockrandt/genmap.},
     author = {Knut Reinert and Costas S Iliopoulos and Mai Alzamel and Christopher Pockrandt and Jinbo
      Xu},
     journal = {Bioinformatics},
     month = {April},
     number = {12},
     pages = {3687--3692},
     publisher = {Oxford University Press, Oxford Academic},
     title = {GenMap: ultra-fast computation of genome mappability},
     url = {http://publications.imp.fu-berlin.de/2515/},
     volume = {36},
     year = {2020}
    }
  • Alexander Schönhuth, M-Hossein Moeinzadeh, Jun Yang, Evgeny Muzychenko, Giuseppe Gallone, David Heller, Knut Reinert, Stefan Haas, Martin Vingron, “Ranbow: A fast and accurate method for polyploid haplotype reconstruction”, vol. 16, iss. 5, 2020-05-29.
    cite this publication
    @article{fu_mi_publications2516,
     abstract = {Reconstructing haplotypes from sequencing data is one of the major challenges in
      genetics. Haplotypes play a crucial role in many analyses, including genome-wide association
      studies and population genetics. Haplotype reconstruction becomes more difficult for higher
      numbers of homologous chromosomes, as it is often the case for polyploid plants. This complexity
      is compounded further by higher heterozygosity, which denotes the frequent presence of variants
      between haplotypes. We have designed Ranbow, a new tool for haplotype reconstruction of polyploid
      genome from short read sequencing data. Ranbow integrates all types of small variants in bi- and
      multi-allelic sites to reconstruct haplotypes. To evaluate Ranbow and currently available
      competing methods on real data, we have created and released a real gold standard dataset from
      sweet potato sequencing data. Our evaluations on real and simulated data clearly show Ranbow?s
      superior performance in terms of accuracy, haplotype length, memory usage, and running time.
      Specifically, Ranbow is one order of magnitude faster than the next best method. The efficiency
      and accuracy of Ranbow makes whole genome haplotype reconstruction of complex genome with higher
      ploidy feasible.},
     author = {Alexander Sch{\"o}nhuth and M-Hossein Moeinzadeh and Jun Yang and Evgeny Muzychenko and
      Giuseppe Gallone and David Heller and Knut Reinert and Stefan Haas and Martin Vingron},
     journal = {PLOS Computational Biology},
     month = {May},
     number = {5},
     pages = {e1007843},
     publisher = {PLOS},
     title = {Ranbow: A fast and accurate method for polyploid haplotype reconstruction},
     url = {http://publications.imp.fu-berlin.de/2516/},
     volume = {16},
     year = {2020}
    }
  • Franziska Hufsky, Kevin Lamkiewicz, Alexandre Almeida, Abdel Aouacheria, Cecilia Arighi, Alex Bateman, Jan Baumbach, Niko Beerenwinkel, Christian Brandt, Marco Cacciabue, Sara Chuguransky, Oliver Drechsel, Robert D Finn, Adrian Fritz, Stephan Fuchs, Georges Hattab, Anne-Christin Hauschild, Dominik Heider, Marie Hoffmann, Martin Hölzer, Stefan Hoops, Lars Kaderali, Ioanna Kalvari, Max von Kleist, RenĂł Kmiecinski, Denise KĂŒhnert, Gorka Lasso, Pieter Libin, Markus List, Hannah F Löchel, Maria J Martin, Roman Martin, Julian Matschinske, Alice C McHardy, Pedro Mendes, Jaina Mistry, Vincent Navratil, Eric P Nawrocki, Áine Niamh O’Toole, Nancy Ontiveros-Palacios, Anton I Petrov, Guillermo Rangel-Pineros, Nicole Redaschi, Susanne Reimering, Knut Reinert, Alejandro Reyes, Lorna Richardson, David L Robertson, Sepideh Sadegh, Joshua B Singer, Kristof Theys, Chris Upton, Marius Welzel, Lowri Williams, Manja Marz, “Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research”, vol. 22, iss. 2, 2020-11-04.
    cite this publication
    @article{fu_mi_publications2517,
     abstract = {SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the
      family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of
      coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly
      for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast
      detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it
      is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this
      review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2
      infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and
      evaluation of containment measures, the study of coronavirus evolution, the discovery of potential
      drug targets and development of therapeutic strategies. For each tool, we briefly describe its use
      case and how it advances research specifically for SARS-CoV-2. All tools are free to use and
      available online, either through web applications or public code repositories.},
     author = {Franziska Hufsky and Kevin Lamkiewicz and Alexandre Almeida and Abdel Aouacheria and
      Cecilia Arighi and Alex Bateman and Jan Baumbach and Niko Beerenwinkel and Christian Brandt and
      Marco Cacciabue and Sara Chuguransky and Oliver Drechsel and Robert D Finn and Adrian Fritz and
      Stephan Fuchs and Georges Hattab and Anne-Christin Hauschild and Dominik Heider and Marie Hoffmann
      and Martin H{\"o}lzer and Stefan Hoops and Lars Kaderali and Ioanna Kalvari and Max von Kleist and
      Ren{\'o} Kmiecinski and Denise K{\"u}hnert and Gorka Lasso and Pieter Libin and Markus List and
      Hannah F L{\"o}chel and Maria J Martin and Roman Martin and Julian Matschinske and Alice C McHardy
      and Pedro Mendes and Jaina Mistry and Vincent Navratil and Eric P Nawrocki and {\'A}ine Niamh
      O?Toole and Nancy Ontiveros-Palacios and Anton I Petrov and Guillermo Rangel-Pineros and Nicole
      Redaschi and Susanne Reimering and Knut Reinert and Alejandro Reyes and Lorna Richardson and David
      L Robertson and Sepideh Sadegh and Joshua B Singer and Kristof Theys and Chris Upton and Marius
      Welzel and Lowri Williams and Manja Marz},
     journal = {Briefings in Bioinformatics},
     keywords = {virus bioinformatics, SARS-CoV-2, sequencing, epidemiology, drug design, tools},
     month = {November},
     number = {2},
     pages = {642--663},
     publisher = {Oxford University Press, Public Health Emergency Collection},
     title = {Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and
      coronavirus research},
     url = {http://publications.imp.fu-berlin.de/2517/},
     volume = {22},
     year = {2020}
    }
  • Natalie Witt, Sandro Andreotti, Anne Busch, Kerstin Neubert, Knut Reinert, Herbert Tomaso, David Meierhofer, “Rapid and Culture Free Identification of Francisella in Hare Carcasses by High-Resolution Tandem Mass Spectrometry Proteotyping”, vol. 11, 2020-05-08.
    cite this publication
    @article{fu_mi_publications2518,
     abstract = {Zoonotic pathogens that can be transmitted via food to humans have a high potential for
      large-scale emergencies, comprising severe effects on public health, critical infrastructures, and
      the economy. In this context, the development of laboratory methods to rapidly detect zoonotic
      bacteria in the food supply chain, including high-resolution mass spectrometry proteotyping are
      needed. In this work, an optimized sample preparation method for liquid chromatography-tandem mass
      spectrometry (LC-MS/MS)-based proteome profiling was established for Francisella isolates, and a
      cluster analysis, as well as a phylogenetic tree, was generated to shed light on evolutionary
      relationships. Furthermore, this method was applied to tissues of infected hare carcasses from
      Germany. Even though the non-informative data outnumbered by a manifold the information of the
      zoonotic pathogen in the resulting proteome profiles, the standardized evaluation of MS data
      within an established automated analysis pipeline identified Francisella (F.) tularensis and,
      thus, could be, in principle, an applicable method to monitor food supply chains.},
     author = {Natalie Witt and Sandro Andreotti and Anne Busch and Kerstin Neubert and Knut Reinert and
      Herbert Tomaso and David Meierhofer},
     journal = {Frontiers in Microbiology},
     month = {May},
     publisher = {Frontiers Media},
     title = {Rapid and Culture Free Identification of Francisella in Hare Carcasses by High-Resolution
      Tandem Mass Spectrometry Proteotyping},
     url = {http://publications.imp.fu-berlin.de/2518/},
     volume = {11},
     year = {2020}
    }
  • Evgenia Ntini, Stefan Budach, Ulf A Vang Ørom, Annalisa Marsico, “Predictive modeling of long non-coding RNA chromatin (dis-)association”, 2020-12-17.
    cite this publication
    @article{fu_mi_publications2572,
     abstract = {Long non-coding RNAs (lncRNAs) are involved in gene expression regulation in cis and
      trans. Although enriched in the chromatin cell fraction, to what degree this defines their broad
      range of functions remains unclear. In addition, the factors that contribute to lncRNA chromatin
      tethering, as well as the molecular basis of efficient lncRNA chromatin dissociation and its
      functional impact on enhancer activity and target gene expression, remain to be resolved. Here, we
      combine pulse-chase metabolic labeling of nascent RNA with chromatin fractionation and transient
      transcriptome sequencing to follow nascent RNA transcripts from their co-transcriptional state to
      their release into the nucleoplasm. By incorporating functional and physical characteristics in
      machine learning models, we find that parameters like co-transcriptional splicing contributes to
      efficient lncRNA chromatin dissociation. Intriguingly, lncRNAs transcribed from enhancer-like
      regions display reduced chromatin retention, suggesting that, in addition to splicing, lncRNA
      chromatin dissociation may contribute to enhancer activity and target gene expression.},
     author = {Evgenia Ntini and Stefan Budach and Ulf A Vang {\O}rom and Annalisa Marsico},
     booktitle = {Predictive modeling of long non-coding RNA chromatin (dis-)association},
     journal = {bioRxiv},
     month = {December},
     publisher = {Cold Spring Harbor Laboratory},
     title = {Predictive modeling of long non-coding RNA chromatin (dis-)association},
     url = {http://publications.imp.fu-berlin.de/2572/},
     year = {2020}
    }
  • Sabrina Krakau, “Statistical models to capture protein-RNA interaction footprints from truncation-based CLIP-seq data”, 2020-01-15.
    cite this publication
    @phdthesis{fu_mi_publications2848,
     abstract = {Protein-RNA interactions play an important role in all post-transcriptional regulatory
      processes. High throughput detection of protein-RNA interactions has been facilitated by the
      emerging CLIP-seq (crosslinking and immunoprecipitation combined with high-throughput sequencing)
      techniques. Enrichments in mapped reads as well as base transitions or deletions at crosslink
      sites can be used to infer binding regions. Single-nucleotide resolution techniques (iCLIP and
      eCLIP) have been achieved by capturing high fractions of cDNAs which are truncated at protein-RNA
      crosslink sites. Increasing numbers of datasets and derivatives of these protocols have been
      published in recent years, requiring tailored computational analyses. Existing methods
      unfortunately do not explicitly model the specifics of truncation patterns and possible biases
      caused by background binding or crosslinking sequence preferences. We present PureCLIP, a hidden
      Markov model based approach, which simultaneously performs peak calling and individual crosslink
      site detection. It is capable of incorporating external data to correct for non-specific
      background signals and, for the first time, for the crosslinking biases. We devised a
      comprehensive evaluation based on three strategies. Firstly, we developed a workflow to simulate
      iCLIP data, which starts from real RNA-seq data and known binding regions and then mimics the
      experimental steps of the iCLIP protocol, including the generation of background signals.
      Secondly, we used experimental iCLIP and eCLIP datasets, using the proteins? known predominant
      binding regions. And thirdly, we assessed the agreement of called sites between replicates,
      assuming target-specific signals are reproducible between replicates. On both simulated and real
      data, PureCLIP is consistently more precise in calling crosslink sites than other state-of-the-art
      methods. In particular when incorporating input control data and crosslink associated motifs
      (CL-motifs) PureCLIP is up to 13\% more precise than other methods and we show that it has an up
      to 20\% higher agreement across replicates. Moreover, our method can optionally merge called
      crosslink sites to binding regions based on their distance and we show that the resulting regions
      reflect the known binding regions with high-resolution. Additionally, we demonstrate that our
      method achieves a high precision robustly over a range of different settings and performs well for
      proteins with different binding characteristics. Lastly, we extended the method to include
      individual CLIP replicates and show that this can boost the precision even further. PureCLIP and
      its documenta- tion are publicly available at https://github.com/skrakau/PureCLIP.},
     author = {Sabrina Krakau},
     month = {January},
     school = {Freie Universit{\"a}t Berlin},
     title = {Statistical models to capture protein-RNA interaction footprints from truncation-based
      CLIP-seq data},
     url = {http://publications.imp.fu-berlin.de/2848/},
     year = {2020}
    }
  • Marten JĂ€ger, “Annotation und Interpretation von Varianten und Polymorphismen im humanen Genom”, 2020-03-09.
    cite this publication
    @phdthesis{fu_mi_publications2853,
     abstract = {Das Gesamtvolumen genomischer Sequenzierungsdaten nimmt, dank der Entwicklung der
      DNA-Hochdurchsatz-Sequenziertechniken, in den letzten Jahren in unglaublichem Tempo zu. Dies
      erweitert unser Wissen des humanen Genoms {\"u}ber dessen Aufbau, die Struktur und die
      r{\"a}umliche Organisation. Die Erkenntnis um den komplexen Aufbau wird in naher Zukunft in die
      Interpretation von Variationen auch im klinischen Kontext einflie{\ss}en m{\"u}ssen, birgt sie
      doch zahlreiche potentielle M{\"o}glichkeiten in der Diagnostik. Whole Genome Sequencing hat schon
      jetzt den Sprung aus den Forschungslaboren in die angewandte Diagnostik von Krankenh{\"a}usern
      geschafft und erlaubt damit die Einf{\"u}hrung der Pr{\"a}zisionsmedizin f{\"u}r alle Patienten.
      F{\"u}r eine optimale klinische Interpretation genomischer Varianten ist es wichtig, konsistente
      und passende Referenzen zu verwenden. Hierzu z{\"a}hlt neben der Auswahl des Referenzgenoms auch
      die verwendete Datenbank zur Annotierung von funktionalen Einheiten auf der DNA. Diese Arbeit geht
      auf zwei wichtige Schritte auf dem Weg zum Einsatz des WGS im klinischen Alltag ein. Der erste
      Schritt beinhaltet, m{\"o}glichst schnell die gefundenen Varianten zu genomischen Eigenschaften
      und Featu- res (in Relation zu einer Referenz) zuzuordnen. Dies ist aufgrund der gro{\ss}en
      Datenmengen ein zunehmendes Problem geworden. Mit Jannovar wird hier eine Softwarebibliothek
      vorgestellt, welche hervorragend an diese Anspr{\"u}che angepasst ist. Die Bibliothek ist schnell,
      flexibel und kann leicht in Annotationspipelines und eigene Programme integriert werden. Die so
      annotierten und charakterisierten Ver{\"a}nderungen des Genotyps bilden eine Basis f{\"u}r die
      weitere Interpretation und Beurteilung durch andere Programme. Die Repr{\"a}sentation der
      Genomreferenz entwickelt sich hin zu einem Graphengenom, um die populationsspezifische
      Variabilit{\"a}t zumindest ansatzweise abzubilden. Diese kann einen enormen Einfluss auf die
      Interpretation von Varianten haben. Im zweiten Schritt geht es darum, diese populationsspezifische
      Komplexit{\"a}t zu erl{\"a}utern. Mit ASDPex wird ein heuristischer Algorithmus vorgestellt,
      welcher f{\"u}r WGS-Daten eines Individuums das Auftreten von alternativen Haplotypsequenzen
      vorhersagt. Daf{\"u}r verwendet es die Verteilung der Allelfrequenzen der individuellen Varianten
      und gleicht sie mit einer Art Fingerabdruck aus haplotypspezifischen Varianten ab. Das Wissen um
      die alternativen Sequenzen kann die Verl{\"a}sslichkeit der klinischen Interpretation weiter
      verbessern. Zuk{\"u}nftig wird es darum gehen, noch mehr Daten in die Varianteninterpretation zu
      integrieren, um noch mehr falsch positive/falsch negative Assoziationen zu verhindern und
      irrelevante Varianten herauszufiltern.},
     author = {Marten J{\"a}ger},
     month = {March},
     school = {Freie Universit{\"a}t Berlin},
     title = {Annotation und Interpretation von Varianten und Polymorphismen im humanen Genom},
     url = {http://publications.imp.fu-berlin.de/2853/},
     year = {2020}
    }

2019

  • Laurence O. W. Wilson, Sara Hetzel, Christopher Pockrandt, Knut Reinert, Denis C. Bauer, “VARSCOT: variant-aware detection and scoring enables sensitive and personalized off-target detection for CRISPR-Cas9”, vol. 19, iss. 1, 2019-06-27.
    cite this publication
    @article{fu_mi_publications2430,
     abstract = {Background Natural variations in a genome can drastically alter the CRISPR-Cas9
      off-target landscape by creating or removing sites. Despite the resulting potential side-effects
      from such unaccounted for sites, current off-target detection pipelines are not equipped to
      include variant information. To address this, we developed VARiant-aware detection and SCoring of
      Off-Targets (VARSCOT). Results VARSCOT identifies only 0.6\% of off-targets to be common between 4
      individual genomes and the reference, with an average of 82\% of off-targets unique to an
      individual. VARSCOT is the most sensitive detection method for off-targets, finding 40 to 70\%
      more experimentally verified off-targets compared to other popular software tools and its machine
      learning model allows for CRISPR-Cas9 concentration aware off-target activity scoring. Conclusions
      VARSCOT allows researchers to take genomic variation into account when designing individual or
      population-wide targeting strategies. VARSCOT is available from
      https://github.com/BauerLab/VARSCOT.},
     author = {Laurence O. W. Wilson and Sara Hetzel and Christopher Pockrandt and Knut Reinert and
      Denis C. Bauer},
     journal = {BMC Biotechnology},
     keywords = {CRISPR-Cas9, Off-target detection, Variants, Genome editing},
     month = {June},
     number = {1},
     title = {VARSCOT: variant-aware detection and scoring enables sensitive and personalized off-target
      detection for CRISPR-Cas9},
     url = {http://publications.imp.fu-berlin.de/2430/},
     volume = {19},
     year = {2019}
    }
  • Enrico Seiler, Kathrin Trappe, Bernhard Y. Renard, “Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation”, vol. 15, iss. 7, 2019-07-23.
    cite this publication
    @article{fu_mi_publications2434,
     abstract = {Horizontal gene transfer (HGT) has changed the way we regard evolution. Instead of
      waiting for the next generation to establish new traits, especially bacteria are able to take a
      shortcut via HGT that enables them to pass on genes from one individual to another, even across
      species boundaries. The tool Daisy offers the first HGT detection approach based on read mapping
      that provides complementary evidence compared to existing methods. However, Daisy relies on the
      acceptor and donor organism involved in the HGT being known. We introduce DaisyGPS, a
      mapping-based pipeline that is able to identify acceptor and donor reference candidates of an HGT
      event based on sequencing reads. Acceptor and donor identification is akin to species
      identification in metagenomic samples based on sequencing reads, a problem addressed by
      metagenomic profiling tools. However, acceptor and donor references have certain properties such
      that these methods cannot be directly applied. DaisyGPS uses MicrobeGPS, a metagenomic profiling
      tool tailored towards estimating the genomic distance between organisms in the sample and the
      reference database. We enhance the underlying scoring system of MicrobeGPS to account for the
      sequence patterns in terms of mapping coverage of an acceptor and donor involved in an HGT event,
      and report a ranked list of reference candidates. These candidates can then be further evaluated
      by tools like Daisy to establish HGT regions. We successfully validated our approach on both
      simulated and real data, and show its benefits in an investigation of an outbreak involving
      Methicillin-resistant Staphylococcus aureus data. Author summary Evolution is traditionally viewed
      as a process where changes are only vertically inherited from parent to offspring across
      generations. Many principles such as phylogenetic trees and even the ?tree of life? are based on
      that doctrine. The concept of horizontal gene transfer changed the way we regard evolution
      completely. Horizontal gene transfer is the movement of genetic information between distantly
      related organisms of the same generation. Genome sequencing not only provided further evidence
      complementing experimental evidence but also shed light onto the frequency and prominence of this
      concept. Especially the rapid spread of antimicrobial resistance genes is a prominent example for
      the impact that horizontal gene transfer can have for public health. Next generation sequencing
      brought means for quick and relatively cheap analysis of even complex metagenomic samples where
      horizontal gene transfer is bound to happen frequently. Methods to directly detect and
      characterise horizontal gene transfer from such sequencing data, however, are still lacking. We
      here provide a method to identify organisms potentially involved in horizontal gene transfer
      events to be used in downstream analysis that enables a characterisation of a horizontal gene
      transfer event in terms of impact and prevalence.},
     author = {Enrico Seiler and Kathrin Trappe and Bernhard Y. Renard},
     journal = {PLOS Computational Biology},
     month = {July},
     number = {7},
     pages = {e1007208},
     publisher = {Public Library of Science},
     title = {Where did you come from, where did you go: Refining metagenomic analysis tools for
      horizontal gene transfer characterisation},
     url = {http://publications.imp.fu-berlin.de/2434/},
     volume = {15},
     year = {2019}
    }
  • Christopher Maximilian Pockrandt, “Approximate String Matching - Improving Data Structures and Algorithms”, 2019-04-15.
    cite this publication
    @phdthesis{fu_mi_publications2523,
     abstract = {This thesis addresses important algorithms and data structures used in sequence
      analysis for applications such as read mapping. First, we give an overview on state-of-the-art FM
      indices and present the latest improvements. In particular, we will introduce a recently published
      FM index based on a new data structure: EPR dictionaries. This rank data structures allows search
      steps in constant time for unidirectional and bidirectional FM indices. To our knowledge this is
      the first and only constant-time implementation of a bidirectional FM index at the time of
      writing. We show that its running time is not only optimal in theory, but currently also
      outperforms all available FM index implementations in practice. Second, we cover approximate
      string matching in bidirectional indices. To improve the running time and make higher error rates
      suitable for index-based searches, we introduce an integer linear program for finding optimal
      search strategies. We show that it is significantly faster than other search strategies in indices
      and cover additional improvements such as hybrid approaches of index-based searches with in-text
      verification, i.e., at some point the partially matched string is located and verified directly in
      the text. Finally, we present a yet unpublished algorithm for fast computation of the mappability
      of genomic sequences. Mappability is a measure for the uniqueness of a genome by counting how
      often each \$k\$-mer of the sequence occurs with a certain error threshold in the genome itself.
      We suggest two applications of mappability with prototype implementations: First, a read mapper
      incorporating the mappability information to improve the running time when mapping reads that
      match highly repetitive regions, and second, we use the mappability information to identify
      phylogenetic markers in a set of similar strains of the same species by the example of E. coli.
      Unique regions allow identifying and distinguishing even highly similar strains using unassembled
      sequencing data. The findings in this thesis can speed up many applications in bioinformatics as
      we demonstrate for read mapping and computation of mappability, and give suggestions for further
      research in this field.},
     author = {Christopher Maximilian Pockrandt},
     month = {April},
     school = {Freie Universit{\"a}t Berlin},
     title = {Approximate String Matching - Improving Data Structures and Algorithms},
     url = {http://publications.imp.fu-berlin.de/2523/},
     year = {2019}
    }
  • Temesgen Hailemariam Dadi, “Whole Genome Shotgun Sequencing Based Taxonomic Profiling Methods for Comparative Study of Microbial Communities”, 2019-05-03.
    cite this publication
    @phdthesis{fu_mi_publications2524,
     abstract = {Microorganisms, typically occurring as large, species diverse communities, are a
      ubiquitous part of nature. These communities are a vital part of their environment, influencing it
      through various layers of interaction. Host-associated microbial communities are particularly
      scrutinized for their influence on the host?s health. Additionally, there is a growing interest in
      microbial communities due to their role in livestock, agriculture, waste treatment, mining, and
      biotechnology. Metagenomics is a relatively young scientific field that aims to study such
      microbial communities based on genetic material recovered directly from an environment. Advances
      in DNA sequencing have enabled us to perform taxonomic profiling, i.e. to identify microbial
      species quantitatively and qualitatively at increasing depth. In whole genome shotgun sequencing
      (WGS), environmental DNA is taken directly from an environment and sequenced after being
      fragmented, without PCR amplification. Taxonomic profiling methods based on such sequencing data
      introduce less PCR bias compared to their amplicon based counterparts such as 16S-rDNA based
      profiling methods. However, the challenges posed by the enormous and redundancy of databases and
      the high degree homology among reference genomes of microorganisms put WGS methods at a
      disadvantage. In this thesis, we will present and discuss two separate computational methods that
      address both challenges. The first method is a taxonomic profiler that leverages coverage
      landscapes created by mapping sequencing reads across reference genomes to address the challenge
      posed by homologous regions of genomes. By carefully evaluating the coverage profile of reference
      genomes we drop spurious references from consideration. This filtration strategy results in more
      uniquely mapping reads to the remaining reference genomes improving both the resolution and
      accuracy of the taxonomic profiling process. We have also shown that this method improves the
      quality of relative abundances assigned to each detected member organism. The second method is a
      distributed read mapper which addresses the issue of large and frequently changing databases by
      systematically partitioning it into smaller bins. It significantly reduces the time, and
      computational resources required to build indices from such large databases by orders of
      magnitudes and updates can be performed very quickly in a few minutes compared to days in earlier
      methods. To achieve a competitive mapping speed while maintaining many small indices, we
      implemented a novel, fast and lightweight filtering data structure called interleaved bloom
      filter. With that, we are able to achieve the described improvements in the index building and
      updating time without compromising the read-mapping speed.},
     author = {Temesgen Hailemariam Dadi},
     month = {May},
     school = {Freie Universit{\"a}t Berlin},
     title = {Whole Genome Shotgun Sequencing Based Taxonomic Profiling Methods for Comparative Study of
      Microbial Communities},
     url = {http://publications.imp.fu-berlin.de/2524/},
     year = {2019}
    }
  • Ulrike Löber, “Development of Bioinformatic Tools for Retroviral Analysis from High Throughput Sequence Data”, 2019-06-26.
    cite this publication
    @phdthesis{fu_mi_publications2533,
     abstract = {For hundreds of millions of years, retroviruses have been integrating into genomes of
      vertebrates. This thesis contributes to the development of new methods for retrieval,
      characterization and the comparison of viruses that have integrated into the genome (endogenous
      retroviruses, or ERVs) and their integration sites in host genomes. The koala retrovirus is an
      outstanding study subject since it is currently in the transition from an exogenous to an
      endogenous retrovirus. In the past decades, high-throughput sequencing (HTS) has allowed
      scientists to investigate genomic data at high coverage and low costs. However, the development of
      new sequencing technologies facilitated the production of vast amounts of data. The analysis
      bottleneck has shifted from data production to the analysis of so-called ?big data?. In
      consequence, new algorithms and pipelines need to be established to process biological data.
      Solutions for automated handling of short-read HTS data exist for many problems and can be
      improved and extended. Recent improvements in HTS resulting in longer sequence fragments have
      helped solve problems connected to short-read sequencing but produced new challenges for genomics
      data processing. In this thesis, I present pipelines to comprehensively profile endogenous
      retroviruses from short-read HTS data for museum koala samples (ancient DNA) and describe a new
      method to amplify retroviral integration sites facilitating long-read HTS. The thesis is divided
      into five sections. In the first part, I describe the biological problem, the evolution of
      sequencing technologies, resulting in information technology problems and proposed solutions
      (chapter 1). In the second chapter, I present a comparison of three different target enrichment
      techniques to retrieve retroviral integration sites from museum koala samples. The computational
      pipeline I developed for this purpose is presented. In chapter 3 I describe a method (sonication
      inverse polymerase chain reaction) for target enrich- ment of long sequence fragments to exploit
      the capacities of third-generation sequencing technologies. An analysis pipeline for the
      processing of sonication inverse PCR products was established. Moreover, the remaining problems
      resulting from artificial read structures are discussed. In chapter 4 the method described in
      chapter 3 was used to profile koala retrovirus integrations. The striking discovery of a new
      retroviral recombinant in koalas is reported. Finally, I discuss our findings and compare short-
      and long-read HTS technologies. An outlook for further applications and remaining computational
      problems is outlined. Overall, this thesis contributes to the automated computational processing
      of HTS data from target enrichment techniques to profile endogenous retroviruses in host
      genomes.},
     author = {Ulrike L{\"o}ber},
     month = {June},
     school = {Freie Universit{\"a}t Berlin},
     title = {Development of Bioinformatic Tools for Retroviral Analysis from High Throughput Sequence
      Data},
     url = {http://publications.imp.fu-berlin.de/2533/},
     year = {2019}
    }

2018

  • T. Marschall, K. Reinert, (59 authors in total) others, “Computational pan-genomics: status, promises and challenges”, vol. 19, iss. 1, 2018-01-01.
    cite this publication
    @article{fu_mi_publications1981,
     abstract = {Many disciplines, from human genetics and oncology to plant breeding, microbiology and
      virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case
      of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next
      few years. Simply scaling up established bioinformatics pipelines will not be sufficient for
      leveraging the full potential of such rich genomic data sets. Instead, novel, qualitatively
      different computational methods and paradigms are needed. We will witness the rapid extension of
      computational pan-genomics, a new sub-area of research in computational biology. In this article,
      we generalize existing definitions and understand a pan-genome as any collection of genomic
      sequences to be analyzed jointly or to be used as a reference. We examine already available
      approaches to construct and use pan-genomes, discuss the potential benefits of future technologies
      and methodologies and review open challenges from the vantage point of the above-mentioned
      biological disciplines. As a prominent example for a computational paradigm shift, we particularly
      highlight the transition from the representation of reference genomes as strings to
      representations as graphs. We outline how this and other challenges from different application
      domains translate into common computational problems, point out relevant bioinformatics techniques
      and identify open problems in computer science. With this review, we aim to increase awareness
      that a joint approach to computational pan-genomics can help address many of the problems
      currently faced in various domains.},
     author = {T. Marschall and K. Reinert and (59 authors in total) others},
     journal = {Briefings in Bioinformatics},
     month = {January},
     number = {1},
     pages = {118--135},
     publisher = {Oxford University Press},
     title = {Computational pan-genomics: status, promises and challenges},
     url = {http://publications.imp.fu-berlin.de/1981/},
     volume = {19},
     year = {2018}
    }
  • RenĂ© Rahn, Stefan Budach, Pascal Costanza, Marcel Ehrhardt, Jonny Hancox, Knut Reinert, “Generic accelerated sequence alignment in SeqAn using vectorization and multi-threading”, vol. 34, iss. 20, 2018-10-15.
    cite this publication
    @article{fu_mi_publications2253,
     abstract = {Motivation Pairwise sequence alignment is undoubtedly a central tool in many
      bioinformatics analyses. In this paper, we present a generically accelerated module for pairwise
      sequence lignments applicable for a broad range of applications. In our module, we unified the
      standard dynamic programming kernel used for pairwise sequence alignments and extended it with a
      generalized inter-sequence vectorization layout, such that many alignments can be computed
      simultaneously by exploiting SIMD (Single Instruction Multiple Data) instructions of modern
      processors. We then extended the module by adding two layers of thread-level parallelization,
      where we a) distribute many independent alignments on multiple threads and b) inherently
      parallelize a single alignment computation using a work stealing approach producing a dynamic
      wavefront progressing along the minor diagonal. Results We evaluated our alignment vectorization
      and parallelization on different processors, including the newest Intel? Xeon? (Skylake) and
      Intel? Xeon Phi? (KNL) processors, and use cases. The instruction set AVX512-BW (Byte and Word),
      available on Skylake processors, can genuinely improve the performance of vectorized alignments.
      We could run single alignments 1600 times faster on the Xeon Phi? and 1400 times faster on the
      Xeon? than executing them with our previous sequential alignment module. Availability The module
      is programmed in C++ using the SeqAn (Reinert et al., 2017) library and distributed with version
      2.4. under the BSD license. We support SSE4, AVX2, AVX512 instructions and included UME::SIMD, a
      SIMD-instruction wrapper library, to extend our module for further instruction sets. We thoroughly
      test all alignment components with all major C++ compilers on various platforms.},
     author = {Ren{\'e} Rahn and Stefan Budach and Pascal Costanza and Marcel Ehrhardt and Jonny Hancox
      and Knut Reinert},
     journal = {Bioinformatics},
     month = {October},
     number = {20},
     pages = {3437--3445},
     publisher = {Oxford Academic (OUP)},
     title = {Generic accelerated sequence alignment in SeqAn using vectorization and multi-threading},
     url = {http://publications.imp.fu-berlin.de/2253/},
     volume = {34},
     year = {2018}
    }
  • Temesgen Hailemariam Dadi, Enrico Siragusa, Vitor C Piro, Andreas Andrusch, Enrico Seiler, Bernhard Y Renard, Knut Reinert, “DREAM-Yara: an exact read mapper for very large databases with short update time”, vol. 34, iss. 17, 2018-09-08.
    cite this publication
    @article{fu_mi_publications2282,
     abstract = {Motivation Mapping-based approaches have become limited in their application to very
      large sets of references since computing an FM-index for very large databases (e.g.
      {\ensuremath{>}}10 GB) has become a bottleneck. This affects many analyses that need such index as
      an essential step for approximate matching of the NGS reads to reference databases. For instance,
      in typical metagenomics analysis, the size of the reference sequences has become prohibitive to
      compute a single full-text index on standard machines. Even on large memory machines, computing
      such index takes about 1 day of computing time. As a result, updates of indices are rarely
      performed. Hence, it is desirable to create an alternative way of indexing while preserving fast
      search times. Results To solve the index construction and update problem we propose the DREAM
      (Dynamic seaRchablE pArallel coMpressed index) framework and provide an implementation. The main
      contributions are the introduction of an approximate search distributor via a novel use of Bloom
      filters. We combine several Bloom filters to form an interleaved Bloom filter and use this new
      data structure to quickly exclude reads for parts of the databases where they cannot match. This
      allows us to keep the databases in several indices which can be easily rebuilt if parts are
      updated while maintaining a fast search time. The second main contribution is an implementation of
      DREAM-Yara a distributed version of a fully sensitive read mapper under the DREAM framework.
      Availability and implementation: https://gitlab.com/pirovc/dream\_yara/},
     author = {Temesgen Hailemariam Dadi and Enrico Siragusa and Vitor C Piro and Andreas Andrusch and
      Enrico Seiler and Bernhard Y Renard and Knut Reinert},
     journal = {Bioinformatics},
     month = {September},
     number = {17},
     pages = {i766--i772},
     title = {DREAM-Yara: an exact read mapper for very large databases with short update time},
     url = {http://publications.imp.fu-berlin.de/2282/},
     volume = {34},
     year = {2018}
    }
  • Ɓukasz Grzeƛkowiak, Beatriz MartĂ­nez-VallespĂ­n, Temesgen H Dadi, Judith Radloff, Salah Amasheh, Femke-Anouska Heinsen, Andre Franke, Knut Reinert, Wilfried Vahjen, JĂŒrgen Zentek, Robert Pieper, “Formula Feeding Predisposes Neonatal Piglets to Clostridium difficile Gut Infection”, vol. 217, iss. 9, 2018-05-01.
    cite this publication
    @article{fu_mi_publications2283,
     abstract = {Spontaneous outbreaks of Clostridium difficile infection (CDI) occur in neonatal
      piglets, but the predisposing factors are largely not known. To study the conditions for C.
      difficile colonization and CDI development, 48 neonatal piglets were moved into isolators, fed
      bovine milk?based formula, and infected with C. difficile 078. Analyses included clinical scoring;
      measurement of the fecal C. difficile burden, toxin B level, and calprotectin level; and
      postmortem histopathological analysis of colon specimens. Controls were noninfected suckling
      piglets. Fecal specimens from suckling piglets, formula-fed piglets, and formula-fed, C.
      difficile?infected piglets were used for metagenomics analysis. High background levels of C.
      difficile and toxin were detected in formula-fed piglets prior to infection, while suckling
      piglets carried about 3-fold less C. difficile, and toxin was not detected. Toxin level in C.
      difficile?challenged animals correlated positively with C. difficile and calprotectin levels.
      Postmortem signs of CDI were absent in suckling piglets, whereas mesocolonic edema and gas-filled
      distal small intestines and ceca, cellular damage, and reduced expression of claudins were
      associated with animals from the challenge trials. Microbiota in formula-fed piglets was enriched
      with Escherichia, Shigella, Streptococcus, Enterococcus, and Ruminococcus species. Formula-fed
      piglets were predisposed to C. difficile colonization earlier as compared to suckling piglets.
      Infection with a hypervirulent C. difficile ribotype did not aggravate the symptoms of infection.
      Sow-offspring association and consumption of porcine milk during early life may be crucial for the
      control of C. difficile expansion in piglets.},
     author = {{\L}ukasz Grze{\'s}kowiak and Beatriz Mart{\'i}nez-Vallesp{\'i}n and Temesgen H Dadi and
      Judith Radloff and Salah Amasheh and Femke-Anouska Heinsen and Andre Franke and Knut Reinert and
      Wilfried Vahjen and J{\"u}rgen Zentek and Robert Pieper},
     journal = {The Journal of Infectious Diseases},
     month = {May},
     number = {9},
     pages = {1442--1452},
     title = {Formula Feeding Predisposes Neonatal Piglets to Clostridium difficile Gut Infection},
     url = {http://publications.imp.fu-berlin.de/2283/},
     volume = {217},
     year = {2018}
    }
  • Kiavash Kianfar, Christopher Pockrandt, Bahman Torkamandi, Haochen Luo, Knut Reinert, “Optimum Search Schemes for Approximate String Matching Using Bidirectional FM-Index”, 2018-04-14.
    cite this publication
    @article{fu_mi_publications2284,
     abstract = {Finding approximate occurrences of a pattern in a text using a full-text index is a
      central problem in bioinformatics and has been extensively researched. Bidirectional indices have
      opened new possibilities in this regard allowing the search to start from anywhere within the
      pattern and extend in both directions. In particular, use of search schemes (partitioning the
      pattern and searching the pieces in certain orders with given bounds on errors) can yield
      significant speed-ups. However, finding optimal search schemes is a difficult combinatorial
      optimization problem. Here for the first time, we propose a mixed integer program (MIP) capable to
      solve this optimization problem for Hamming distance with given number of pieces. Our experiments
      show that the optimal search schemes found by our MIP significantly improve the performance of
      search in bidirectional FM-index upon previous ad-hoc solutions. For example, approximate matching
      of 101-bp Illumina reads (with two errors) becomes 35 times faster than standard backtracking.
      Moreover, despite being performed purely in the index, the running time of search using our
      optimal schemes (for up to two errors) is comparable to the best state-of-the-art aligners, which
      benefit from combining search in index with in-text verification using dynamic programming. As a
      result, we anticipate a full-fledged aligner that employs an intelligent combination of search in
      the bidirectional FM-index using our optimal search schemes and in-text verification using dynamic
      programming outperforms today's best aligners. The development of such an aligner, called FAMOUS
      (Fast Approximate string Matching using OptimUm search Schemes), is ongoing as our future work.},
     author = {Kiavash Kianfar and Christopher Pockrandt and Bahman Torkamandi and Haochen Luo and Knut
      Reinert},
     booktitle = {Optimum Search Schemes for Approximate String Matching Using Bidirectional FM-Index},
     journal = {bioRxiv, The Preprint Server for Biology},
     month = {April},
     title = {Optimum Search Schemes for Approximate String Matching Using Bidirectional FM-Index},
     url = {http://publications.imp.fu-berlin.de/2284/},
     year = {2018}
    }
  • Anne Busch, Prasad Thomas, Eric Zuchantke, Holger Brendebach, Kerstin Neubert, Josephine Gruetzke, Sascha Al Dahouk, Martin Peters, Helmut Hotzel, Heinrich Neubauer, Herbert Tomaso, “Revisiting Francisella tularensis subsp. holarctica, Causative Agent of Tularemia in Germany With Bioinformatics: New Insights in Genome Structure, DNA Methylation and Comparative Phylogenetic Analysis”, vol. 9, 2018-03-13.
    cite this publication
    @article{fu_mi_publications2374,
     abstract = {Francisella (F.) tularensis is a highly virulent, Gram-negative bacterial pathogen and
      the causative agent of the zoonotic disease tularemia. Here, we generated, analyzed and
      characterized a high quality circular genome sequence of the F. tularensis subsp. holarctica
      strain 12T0050 that caused fatal tularemia in a hare. Besides the genomic structure, we focused on
      the analysis of oriC, unique to the Francisella genus and regulating replication in and outside
      hosts and the first report on genomic DNA methylation of a Francisella strain. The high quality
      genome was used to establish and evaluate a diagnostic whole genome sequencing pipeline. A
      genotyping strategy for F. tularensis was developed using various bioinformatics tools for
      genotyping. Additionally, whole genome sequences of F. tularensis subsp. holarctica isolates
      isolated in the years 2008?2015 in Germany were generated. A phylogenetic analysis allowed to
      determine the genetic relatedness of these isolates and confirmed the highly conserved nature of
      F. tularensis subsp. holarctica.},
     author = {Anne Busch and Prasad Thomas and Eric Zuchantke and Holger Brendebach and Kerstin Neubert
      and Josephine Gruetzke and Sascha Al Dahouk and Martin Peters and Helmut Hotzel and Heinrich
      Neubauer and Herbert Tomaso},
     journal = {Frontiers in Microbiology},
     month = {March},
     title = {Revisiting Francisella tularensis subsp. holarctica, Causative Agent of Tularemia in
      Germany With Bioinformatics: New Insights in Genome Structure, DNA Methylation and Comparative
      Phylogenetic Analysis},
     url = {http://publications.imp.fu-berlin.de/2374/},
     volume = {9},
     year = {2018}
    }
  • Sven-Leon Kuchenbecker, “Analysis of Antigen Receptor Repertoires Captured by High Throughput Sequencing”, 2018-06-11.
    cite this publication
    @phdthesis{fu_mi_publications2535,
     abstract = {In vertebrate species, the main mechanisms of defence against various types of
      pathogens are divided into the innate and the adaptive immune system. While the former relies on
      generic mechanisms, for example to detect the presence of bacterial cells, the latter features
      mechanisms that allow the individual to acquire defenses against specific, potentially novel
      features of pathogens and to maintain them throughout life. In a simplified sense, the adaptive
      immune system continuously generates new defenses against all kinds of structures randomly,
      carefully selecting them not to be reactive against the hosts own cells. The underlying generative
      mechanism is a unique somatic recombination process modifying the genes encoding the proteins
      responsible for the recognition of such foreign structures, the so-called antigen receptors. With
      the advances of high throughput DNA sequencing, we have gained the ability to capture the
      repertoire of different antigen receptor genes that an individual has acquired by selectively
      sequencing the recombined loci from a cell sample. This enables us to examine and explore the
      development and behaviour of the adaptive immune system in a new way, with a variety of potential
      medical applications. The main focus of this thesis is on two computational problems related to
      immune repertoire sequencing. Firstly, we developed a method to properly annotate the raw
      sequencing data that is generated in such experiments, taking into account various sources of
      biases and errors that either generally occur in the context of DNA sequencing or are specific for
      immune repertoire sequencing experiments. We will describe the algorithmic details of this method
      and then demonstrate its superiority in comparison with previously published methods on various
      datasets. Secondly, we developed a machine learning based workflow to interpret this data in the
      sense that we attempted to classify such recombined genes functionally using a previously trained
      model. We implemented alternative models within this workflow, which we will first describe
      formally and then assess their performances on real data in the context of a binary functional
      feature in T cells, namely whether they have differentiated into cytotoxic or helper T cells.},
     author = {Sven-Leon Kuchenbecker},
     month = {June},
     school = {Freie Universit{\"a}t Berlin},
     title = {Analysis of Antigen Receptor Repertoires Captured by High Throughput Sequencing},
     url = {http://publications.imp.fu-berlin.de/2535/},
     year = {2018}
    }
  • Vitor C Piro, “Reference and taxonomy based methods for classification and abundance estimation of organisms in metagenomic samples”, 2018-11-30.
    cite this publication
    @phdthesis{fu_mi_publications2538,
     abstract = {Metagenomics provides the means to study the vast and still mostly unknown microbial
      world which comprises at least half of earth's genetic diversity. Computational metagenomics
      enables those discoveries via analysis of large amounts of data which are being generated in a
      fast pace with high-throughput technologies. Reference-based methods are commonly used to study
      environmental samples based on a set of previously assembled reference sequences which are often
      linked to a taxonomic classification. Finding the origin of each sequenced fragment and profiling
      an environmental sample as a whole are the main goals of binning and taxonomic profiling tools,
      respectively. In this thesis I present three methods in computational metagenomics. Sets of
      curated reference sequences jointly with taxonomic classification are employed to characterize
      community samples. The main goal of those contributions is to improve the state-of-the-art of
      taxonomic profiling and binning, with fast, sensitive and precise methods. First I present ganon,
      a sequence classification tool for metagenomics which works with a very large number of reference
      sequences. Ganon provides an efficient method to index sequences and to keep those indices updated
      in very short time. In addition, ganon performs taxonomic binning with strongly improved precision
      compared to the current available methods. For a general profiling of metagenomic samples and
      abundance estimation I introduce DUDes. Rather than predicting strains in the sample based only on
      relative abundances, DUDes first identifies possible candidates by comparing the strength of
      mapped reads in each node of the taxonomic tree in an iterative top-down manner. This technique
      works in an opposite direction of the lowest common ancestor approach. Lastly, I present MetaMeta,
      a pipeline to execute metagenome analysis tools and integrate their results. MetaMeta is a method
      to combine and enhance results from multiple taxonomic binning and profiling tools and at the same
      time a pipeline to easily execute tools and analyze environmental data. MetaMeta includes database
      generation, pre-processing, execution, and integration steps, allowing easy installation,
      visualization and parallelization of state-of-the-art tools. Using the same input data, MetaMeta
      provides more sensitive and reliable results with the presence of each identified organism being
      supported by several methods. Those three projects introduce new methodologies and improved
      results over similar methods, constituting valuable contributions to characterize communities in a
      reference and taxonomy-based manner.},
     author = {Vitor C Piro},
     month = {November},
     school = {Freie Universit{\"a}t Berlin},
     title = {Reference and taxonomy based methods for classification and abundance estimation of
      organisms in metagenomic samples},
     url = {http://publications.imp.fu-berlin.de/2538/},
     year = {2018}
    }
  • Kathrin Trappe, “Computational Methods for Integrative Structural Variant Analysis Across Species Boundaries”, 2018-11-29.
    cite this publication
    @phdthesis{fu_mi_publications2541,
     abstract = {Structural variations (SVs) are a phenomenon that have a tremendous impact on all
      species. SVs are the result of fundamental rearrangement mechanisms but can lead to severe human
      diseases like cancer. Rearrangement events also provide means that enable bacteria to adapt to
      environmental pressures where they can also happen across species boundaries in events called
      horizontal gene transfer (HGT). The incorporation of foreign genes from a donor into an acceptor
      genome can be investigated on the genomic level, the activity and protein expression changes,
      however, are better revealed on the proteomic level. This thesis contributes four computational
      methods for the detection of complex SVs of various types and sizes including HGT events from
      genomic next-generation sequencing (NGS) data and proteomic shotgun mass-spectrometry (MS) data.
      Concerning HGT events, our methods address the questions of what organisms are involved in the
      transfer, what genes are exactly transferred and to what position, and what are the implications
      on proteomic level. First, we present the generic SV detection tool Gustaf. Gustaf improves the
      size and type resolution compared to previous SV detection methods. A further specific advantage
      is the characterisation of translocations and dispersed duplications as a combination of simple,
      delocalised variants that have to be inferred from separate SV calls. With this basis for a more
      in-depth focus on HGT detection, we developed two mapping-based methods, Daisy and DaisyGPS. Daisy
      facilitates Gustaf and further SV detection strategies to precisely identify the transferred
      region within the donor and its insertion site in the acceptor genome. DaisyGPS uses metagenomic
      profiling strategies to identify suitable acceptor and donor references. In contrast to previous
      approaches based on sequence composition patterns or phylogenetic disagreements, our methods
      provide a detection based on sequence comparison and hence offer novel means of evidence. In the
      last project, we present a method for HGT detection, called Hortense, that is based on proteomic
      MS data. Hortense extends a standard database peptide search with a thorough cross-validation to
      ensure HGT properties, and is the first dedicated proteomics HGT detection method. Results from
      Hortense can also serve as supporting evidence and functional confirmation for HGT events proposed
      by our genomic-based methods. Taken together, the three HGT methods provide a full view of the
      transfer event that was not be possible before or with one of the methods alone.},
     author = {Kathrin Trappe},
     month = {November},
     school = {Freie Universit{\"a}t Berlin},
     title = {Computational Methods for Integrative Structural Variant Analysis Across Species
      Boundaries},
     url = {http://publications.imp.fu-berlin.de/2541/},
     year = {2018}
    }

2017

  • Enrique Audain, Julian Uszkoreit, Timo Sachsenberg, Julianus Pfeuffer, Xiao Liang, Henning Hermjakob, Aniel Sanchez, Martin Eisenacher, Knut Reinert, David L. Tabb, Oliver Kohlbacher, Yasset Perez-Riverol, “In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics”, vol. 150, 2017-01-06.
    cite this publication
    @article{fu_mi_publications1939,
     abstract = {In mass spectrometry-based shotgun proteomics, protein identifications are usually the
      desired result. However, most of the analytical methods are based on the identification of
      reliable peptides and not the direct identification of intact proteins. Thus, assembling peptides
      identified from tandem mass spectra into a list of proteins, referred to as protein inference, is
      a critical step in proteomics research. Currently, different protein inference algorithms and
      tools are available for the proteomics community. Here, we evaluated five software tools for
      protein inference (PIA, ProteinProphet, Fido, ProteinLP, MSBayesPro) using three popular database
      search engines: Mascot, X!Tandem, and MS-GF +. All the algorithms were evaluated using a highly
      customizable KNIME workflow using four different public datasets with varying complexities
      (different sample preparation, species and analytical instruments). We defined a set of quality
      control metrics to evaluate the performance of each combination of search engines, protein
      inference algorithm, and parameters on each dataset. We show that the results for complex samples
      vary not only regarding the actual numbers of reported protein groups but also concerning the
      actual composition of groups. Furthermore, the robustness of reported proteins when using
      databases of differing complexities is strongly dependant on the applied inference algorithm.
      Finally, merging the identifications of multiple search engines does not necessarily increase the
      number of reported proteins, but does increase the number of peptides per protein and thus can
      generally be recommended.},
     author = {Enrique Audain and Julian Uszkoreit and Timo Sachsenberg and Julianus Pfeuffer and Xiao
      Liang and Henning Hermjakob and Aniel Sanchez and Martin Eisenacher and Knut Reinert and David L.
      Tabb and Oliver Kohlbacher and Yasset Perez-Riverol},
     journal = {Journal of Proteomics},
     month = {January},
     pages = {170--182},
     publisher = {Elsevier},
     title = {In-depth analysis of protein inference algorithms using multiple search engines and
      well-defined metrics},
     url = {http://publications.imp.fu-berlin.de/1939/},
     volume = {150},
     year = {2017}
    }
  • B. Vatansever, A. Muñoz, C. L. Klein, K. Reinert, “Development and optimisation of a generic micro LC-ESI-MS method for the qualitative and quantitative determination of 30-mer toxic gliadin peptides in wheat flour for food analysis”, vol. 409, iss. 4, 2017-02.
    cite this publication
    @article{fu_mi_publications1976,
     abstract = {We sometimes see manufactured bakery products on the market which are labelled as being
      gluten free. Why is the content of such gluten proteins of importance for the fabrication of
      bakery industry and for the products? The gluten proteins represent up to 80 \% of wheat proteins,
      and they are conventionally subdivided into gliadins and glutenins. Gliadins belong to the proline
      and glutamine-rich prolamin family. Its role in human gluten intolerance, as a consequence of its
      harmful effects, is well documented in the scientific literature. The only known therapy so far is
      a gluten-free diet, and hence, it is important to develop robust and reliable analytical methods
      to quantitatively assess the presence of the identified peptides causing the so-called coeliac
      disease. This work describes the development of a new, fast and robust micro ion pair-LC-MS
      analytical method for the qualitative and quantitative determination of 30-mer toxic gliadin
      peptides in wheat flour. The use of RapiGest? SF as a denaturation reagent prior to the enzymatic
      digestion showed to shorten the measuring time. During the optimisation of the enzymatic digestion
      step, the best 30-mer toxic peptide was identified from the maximum recovery after 3 h of
      digestion time. The lower limit of quantification was determined to be 0.25
      ng/{\ensuremath{\mu}}L. The method has shown to be linear for the selected concentration range of
      0.25?3.0 ng/{\ensuremath{\mu}}L. The uncertainty related to reproducibility of measurement
      procedure, excluding the extraction step, has shown to be 5.0 \% (N = 12). Finally, this method
      was successfully applied to the quantification of 30-mer toxic peptides from commercial wheat
      flour with an overall uncertainty under reproducibility conditions of 6.4 \% including the
      extraction of the gliadin fraction. The results were always expressed as the average of the values
      from all standard concentrations. Subsequently, the final concentration of the 30-mer toxic
      peptide in the flour was calculated and expressed in milligrams per gram unit. The determined,
      calculated concentration of the 30-mer toxic peptide in the flour was found to be 1.29 {$\pm$}
      0.37 {\ensuremath{\mu}}g/g in flour (N = 25, sy = 545,075, f = 25 ? 2 (t = 2.069), P = 95 \%,
      two-sided).},
     author = {B. Vatansever and A. Mu{\~n}oz and C. L. Klein and K. Reinert},
     journal = {Analytical and Bioanalytical Chemistry},
     month = {February},
     number = {4},
     pages = {989--997},
     publisher = {Springer Berlin Heidelberg},
     title = {Development and optimisation of a generic micro LC-ESI-MS method for the qualitative and
      quantitative determination of 30-mer toxic gliadin peptides in wheat flour for food analysis},
     url = {http://publications.imp.fu-berlin.de/1976/},
     volume = {409},
     year = {2017}
    }
  • Knut Reinert, Temesgen Hailemariam Dadi, Marcel Ehrhardt, Hannes Hauswedell, Svenja Mehringer, RenĂ© Rahn, Jongkyu Kim, Christopher Pockrandt, Jörg Winkler, Enrico Siragusa, Gianvito Urgese, David Weese, “The SeqAn C++ template library for efficient sequence analysis: A resource for programmers”, vol. 261, 2017-11-10.
    cite this publication
    @article{fu_mi_publications2103,
     abstract = {Background The use of novel algorithmic techniques is pivotal to many important
      problems in life science. For example the sequencing of the human genome (Venter et al., 2001)
      would not have been possible without advanced assembly algorithms and the development of practical
      BWT based read mappers have been instrumental for NGS analysis. However, owing to the high speed
      of technological progress and the urgent need for bioinformatics tools, there was a widening gap
      between state-of-the-art algorithmic techniques and the actual algorithmic components of tools
      that are in widespread use. We previously addressed this by introducing the SeqAn library of
      efficient data types and algorithms in 2008 (D{\"o}ring et al., 2008). Results The SeqAn library
      has matured considerably since its first publication 9 years ago. In this article we review its
      status as an established resource for programmers in the field of sequence analysis and its
      contributions to many analysis tools. Conclusions We anticipate that SeqAn will continue to be a
      valuable resource, especially since it started to actively support various hardware acceleration
      techniques in a systematic manner. Keywords NGS analysis; Software libraries; C++; Data
      structures},
     author = {Knut Reinert and Temesgen Hailemariam Dadi and Marcel Ehrhardt and Hannes Hauswedell and
      Svenja Mehringer and Ren{\'e} Rahn and Jongkyu Kim and Christopher Pockrandt and J{\"o}rg Winkler
      and Enrico Siragusa and Gianvito Urgese and David Weese},
     journal = {Journal of Biotechnology},
     keywords = {NGS analysis; Software libraries; C++; Data structures},
     month = {November},
     pages = {157--168},
     publisher = {ELSEVIER},
     title = {The SeqAn C++ template library for efficient sequence analysis: A resource for
      programmers},
     url = {http://publications.imp.fu-berlin.de/2103/},
     volume = {261},
     year = {2017}
    }
  • Julianus Pfeuffer, Timo Sachsenberg, Oliver Alka, Mathias Walzer, Alexander Fillbrunn, Lars Nilse, Oliver Schilling, Knut Reinert, Oliver Kohlbacher, “OpenMS – A platform for reproducible analysis of mass spectrometry data”, vol. 261, 2017-11-10.
    cite this publication
    @article{fu_mi_publications2116,
     abstract = {Background In recent years, several mass spectrometry-based omics technologies emerged
      to investigate qualitative and quantitative changes within thousands of biologically active
      components such as proteins, lipids and metabolites. The research enabled through these methods
      potentially contributes to the diagnosis and pathophysiology of human diseases as well as to the
      clarification of structures and interactions between biomolecules. Simultaneously, technological
      advances in the field of mass spectrometry leading to an ever increasing amount of data, demand
      high standards in efficiency, accuracy and reproducibility of potential analysis software. Results
      This article presents the current state and ongoing developments in OpenMS, a versatile
      open-source framework aimed at enabling reproducible analyses of high-throughput mass spectrometry
      data. It provides implementations of frequently occurring processing operations on MS data through
      a clean application programming interface in C++ and Python. A collection of 185 tools and
      ready-made workflows for typical MS-based experiments enable convenient analyses for
      non-developers and facilitate reproducible research without losing flexibility. Conclusions OpenMS
      will continue to increase its ease of use for developers as well as users with improved continuous
      integration/deployment strategies, regular trainings with updated training materials and multiple
      sources of support. The active developer community ensures the incorporation of new features to
      support state of the art research.},
     author = {Julianus Pfeuffer and Timo Sachsenberg and Oliver Alka and Mathias Walzer and Alexander
      Fillbrunn and Lars Nilse and Oliver Schilling and Knut Reinert and Oliver Kohlbacher},
     journal = {Journal of Biotechnology},
     month = {November},
     pages = {142--148},
     publisher = {ELSEVIER},
     title = {OpenMS ? A platform for reproducible analysis of mass spectrometry data},
     url = {http://publications.imp.fu-berlin.de/2116/},
     volume = {261},
     year = {2017}
    }
  • Johannes T. Roehr, Christoph Dieterich, Knut Reinert, “Flexbar 3.0 – SIMD and multicore parallelization”, vol. 33, iss. 18, 2017-09-15.
    cite this publication
    @article{fu_mi_publications2117,
     abstract = {Motivation: High-throughput sequencing machines can process many samples in a single
      run. For Illumina systems, sequencing reads are barcoded with an additional DNA tag that is
      contained in the respective sequencing adapters. The recognition of barcode and adapter sequences
      is hence commonly needed for the analysis of next-generation sequencing data. Flexbar performs
      demultiplexing based on barcodes and adapter trimming for such data. The massive amounts of data
      generated on modern sequencing machines demand that this preprocessing is done as efficiently as
      possible. Results: We present Flexbar 3.0, the successor of the popular program Flexbar. It
      employs now twofold parallelism: multi-threading and additionally SIMD vectorization. Both types
      of parallelism are used to speed-up the computation of pair-wise sequence alignments, which are
      used for the detection of barcodes and adapters. Furthermore, new features were included to cover
      a wide range of applications. We evaluated the performance of Flexbar based on a simulated
      sequencing dataset. Our program outcompetes other tools in terms of speed and is among the best
      tools in the presented quality benchmark. Availability and implementation:
      https://github.com/seqan/flexbar Contact: johannes.roehr@fu-berlin.de or
      knut.reinert@fu-berlin.de},
     author = {Johannes T. Roehr and Christoph Dieterich and Knut Reinert},
     journal = {Bioinformatics},
     month = {September},
     number = {18},
     pages = {2941--2942},
     title = {Flexbar 3.0 ? SIMD and multicore parallelization},
     url = {http://publications.imp.fu-berlin.de/2117/},
     volume = {33},
     year = {2017}
    }
  • Christopher Pockrandt, Marcel Ehrhardt, Knut Reinert, S. Sahinalp, “EPR-Dictionaries: A Practical and Fast Data Structure for Constant Time Searches in Unidirectional and Bidirectional FM Indices”, vol. 10229, p. 16, 2017-04-12.
    cite this publication
    @incollection{fu_mi_publications2118,
     abstract = {The unidirectional FM index was introduced by Ferragina and Manzini in 2000 and allows
      to search a pattern in the index in one direction. The bidirectional FM index (2FM) was introduced
      by Lam et al. in 2009. It allows to search for a pattern by extending an infix of the pattern
      arbitrarily to the left or right. If {\ensuremath{\sigma}} is the size of the alphabet then the
      method of Lam et al. can conduct one step in time O({\ensuremath{\sigma}}) while needing space
      O({\ensuremath{\sigma}}{$\cdot$}n) using constant time rank queries on bit vectors. Schnattinger
      and colleagues improved this time to O(log{\ensuremath{\sigma}}) while using
      O(log{\ensuremath{\sigma}}{$\cdot$}n) bits of space for both, the FM and 2FM index. This is
      achieved by the use of binary wavelet trees. In this paper we introduce a new, practical method
      for conducting an exact search in a uni- and bidirectional FM index in O(1) time per step while
      using
      O(log{\ensuremath{\sigma}}{$\cdot$}n)+o(log{\ensuremath{\sigma}}{$\cdot$}{\ensuremath{\sigma}}{$\cdot$}n)
      bits of space. This is done by replacing the binary wavelet tree by a new data structure, the
      Enhanced Prefixsum Rank dictionary (EPR-dictionary). We implemented this method in the SeqAn C++
      library and experimentally validated our theoretical results. In addition we compared our
      implementation with other freely available implementations of bidirectional indices and show that
      we are between {$\approx$}2.2?4.2 times faster. This will have a large impact for many
      bioinformatics applications that rely on practical implementations of (2)FM indices e.g. for read
      mapping. To our knowledge this is the first implementation of a constant time method for a search
      step in 2FM indices.},
     author = {Christopher Pockrandt and Marcel Ehrhardt and Knut Reinert},
     booktitle = {Research in Computational Molecular Biology. RECOMB 2017},
     editor = {S. Sahinalp},
     month = {April},
     pages = {190--206},
     publisher = {Springer, Cham},
     series = {Lecture Notes in Computer Science (LNCS)},
     title = {EPR-Dictionaries: A Practical and Fast Data Structure for Constant Time Searches in
      Unidirectional and Bidirectional FM Indices},
     url = {http://publications.imp.fu-berlin.de/2118/},
     volume = {10229},
     year = {2017}
    }
  • Temesgen Hailemariam Dadi, Bernhard Y. Renard, Lothar H. Wieler, Torsten Semmler, Knut Reinert, “SLIMM: species level identification of microorganisms from metagenomes”, vol. 5, 2017-03-28.
    cite this publication
    @article{fu_mi_publications2119,
     abstract = {Identification and quantification of microorganisms is a significant step in studying
      the alpha and beta diversities within and between microbial communities respectively. Both
      identification and quantification of a given microbial community can be carried out using whole
      genome shotgun sequences with less bias than when using 16S-rDNA sequences. However, shared
      regions of DNA among reference genomes and taxonomic units pose a significant challenge in
      assigning reads correctly to their true origins. The existing microbial community profiling tools
      commonly deal with this problem by either preparing signature-based unique references or assigning
      an ambiguous read to its least common ancestor in a taxonomic tree. The former method is limited
      to making use of the reads which can be mapped to the curated regions, while the latter suffer
      from the lack of uniquely mapped reads at lower (more specific) taxonomic ranks. Moreover, even if
      the tools exhibited good performance in calling the organisms present in a sample, there is still
      room for improvement in determining the correct relative abundance of the organisms. We present a
      new method Species Level Identification of Microorganisms from Metagenomes (SLIMM) which addresses
      the above issues by using coverage information of reference genomes to remove unlikely genomes
      from the analysis and subsequently gain more uniquely mapped reads to assign at lower ranks of a
      taxonomic tree. SLIMM is based on a few, seemingly easy steps which when combined create a tool
      that outperforms state-of-the-art tools in run-time and memory usage while being on par or better
      in computing quantitative and qualitative information at species-level.},
     author = {Temesgen Hailemariam Dadi and Bernhard Y. Renard and Lothar H. Wieler and Torsten Semmler
      and Knut Reinert},
     journal = {PeerJ},
     month = {March},
     pages = {e3138},
     title = {SLIMM: species level identification of microorganisms from metagenomes},
     url = {http://publications.imp.fu-berlin.de/2119/},
     volume = {5},
     year = {2017}
    }
  • Russell Schwartz, Knut Reinert, “17th International Workshop on Algorithms in Bioinformatics (WABI 2017)”, vol. 88, p. 394, 2017-08.
    cite this publication
    @book{fu_mi_publications2132,
     abstract = {This proceedings volume contains papers presented at the 17th Workshop on Algorithms in
      Bioinformatics (WABI 2017), which was held in Boston, MA, USA in conjunction with the 8th ACM
      Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB) from August
      21?23, 2017. The Workshop on Algorithms in Bioinformatics is an annual conference established in
      2001 to cover all aspects of algorithmic work in bioinformatics, computational biology, and
      systems biology. The workshop is intended as a forum for discrete algorithms and machine-learning
      methods that address important problems in molecular biology, that are founded on sound models,
      that are computationally efficient, and that have been implemented and tested in simulations and
      on real datasets. The meeting?s focus is on recent research results, including significant
      work-in-progress, as well as identifying and explore directions of future research. WABI 2017 is
      grateful for the support of ACM-BCB in allowing us to cohost the meetings, as well as to ACM-BCB?s
      sponsors: the Association for Computing Machinery (ACM) and ACM?s SIGBIO. In 2017, a total of 55
      manuscripts were submitted to WABI from which 27 were selected for presentation at the conference.
      This year, WABI is adopting a new proceedings form, publishing the conference proceedings through
      the LIPIcs (Leibniz International Proceedings in Informatics) proceedings series. Extended
      versions of selected papers will be invited for publication in a thematic series in the journal
      Algorithms for Molecular Biology (AMB), published by BioMed Central. The 27 papers were selected
      based on a thorough peer review, involving at least three independent reviewers per submitted
      paper, followed by discussions among the WABI Program Committee members. The selected papers cover
      a wide range of topics, including statistical inference, phylogenetic studies, sequence and genome
      analysis, comparative genomics, and mass spectrometry data analysis. We thank all the authors of
      submitted papers and the members of the WABI Program Committee and their reviewers for their
      efforts that made this conference possible. We are also grateful to the WABI Steering Committee
      for their help and advice. We also thank all the conference participants and speakers who
      contribute to a great scientific program. In particular, we are indebted to the keynote speaker of
      the conference, Tandy Warnow, for her presentation. We also thank Christopher Pockrandt for
      setting up the WABI webpage and Umit Acar for his help with coordinating the WABI and ACM-BCB
      pages. Finally, we thank the ACM-BCB Organizing Committee, especially Nurit Haspel and Lenore
      Cowen, for their hard work in making all of the local arrangements and working closely with us to
      ensure a successful and exciting WABI and ACM-BCB.},
     address = {Saarbr{\"u}cken/Wadern},
     editor = {Russell Schwartz and Knut Reinert},
     month = {August},
     publisher = {Dagstuhl LIPIcs},
     series = {LIPICS},
     title = {17th International Workshop on Algorithms in Bioinformatics (WABI 2017)},
     url = {http://publications.imp.fu-berlin.de/2132/},
     volume = {88},
     year = {2017}
    }
  • Jongkyu Kim, Knut Reinert, Russell Schwartz, Knut Reinert, “Vaquita: Fast and Accurate Identification of Structural Variation Using Combined Evidence”, iss. 88, p. 14, 2017-08.
    cite this publication
    @incollection{fu_mi_publications2133,
     abstract = {Motivation: Comprehensive identification of structural variations (SVs) is a crucial
      task for studying genetic diversity and diseases. However, it remains challenging. There is only a
      marginal consensus between different methods, and our understanding of SVs is substantially
      limited.In general, integration of multiple pieces of evidence including split-read, read-pair,
      soft-clip, and read-depth yields the best result regarding accuracy. However, doing this step by
      step is usually cumbersome and computationally expensive. Result: We present Vaquita, an accurate
      and fast tool for the identification of structural variations, which leverages all four types of
      evidence in a single program. After merging SVs from split-reads and discordant read-pairs,
      Vaquita realigns the soft-clipped reads to the selected regions using a fast bit-vector algorithm.
      Furthermore, it also considers the discrepancy of depth distribution around breakpoints using
      Kullback-Leibler divergence. Finally, Vaquita provides an additional metric for candidate
      selection based on voting, and also provides robust prioritization based on rank aggregation. We
      show that Vaquita is robust in terms of sequencing coverage, insertion size of the library, and
      read length, and is comparable or even better for the identification of deletions, inversions,
      duplications, and translocations than state-of-the-art tools, using both simulated and real
      datasets. In addition, Vaquita is more than eight times faster than any other tools in comparison.
      Availability: Vaquita is implemented in C++ using the SeqAn library. The source code is
      distributed under the BSD license and can be downloaded at http://github.com/seqan/vaquita},
     address = {Saarbr{\"u}cken/Wadern},
     author = {Jongkyu Kim and Knut Reinert},
     booktitle = {17th International Workshop on Algorithms in Bioinformatics (WABI 2017)},
     editor = {Russell Schwartz and Knut Reinert},
     month = {August},
     number = {88},
     pages = {185(13:1)--198(13:14)},
     publisher = {Dagstuhl LIPIcs},
     series = {LIPICS},
     title = {Vaquita: Fast and Accurate Identification of Structural Variation Using Combined
      Evidence},
     url = {http://publications.imp.fu-berlin.de/2133/},
     year = {2017}
    }
  • Gene Meyers, Mihai Pop, Knut Reinert, Tandy Warnow, “Dagstuhl Reports, Vol. 6, No. 8, pp. 91-130: Next Generation Sequencing (Dagstuhl Seminar 16351)”, p. 40, 2017.
    cite this publication
    @manual{fu_mi_publications2134,
     abstract = {Next Generation Sequencing (NGS) data have begun to appear in many applications that
      are clinically relevant, such as resequencing of cancer patients, disease-gene discovery and
      diagnostics for rare diseases, microbiome analyses, and gene expression profiling. The analysis of
      sequencing data is demanding because of the enormous data volume and the need for fast turnaround
      time, accuracy, reproducibility, and data security. This Dagstuhl Seminar aimed at a free and deep
      exchange of ideas and needs between the communities of algorithmicists and theoreticians and
      practitioners from the biomedical field. It identified several relevant fields such as data
      structures and algorithms for large data sets, hardware acceleration, new problems in the upcoming
      age of genomes, etc. which were discussed in breakout groups.},
     address = {Dagstuhl, Germany},
     author = {Gene Meyers and Mihai Pop and Knut Reinert and Tandy Warnow},
     number = {DOI: 10.4230/DagRep.6.8.91},
     publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
     title = {Dagstuhl Reports, Vol. 6, No. 8, pp. 91-130: Next Generation Sequencing (Dagstuhl Seminar
      16351)},
     type = {Documentation},
     url = {http://publications.imp.fu-berlin.de/2134/},
     year = {2017}
    }

2016

  • S. Canzar, S. Andreotti, D. Weese, K. Reinert, G. W. Klau, “CIDANE: comprehensive isoform discovery and abundance estimation”, vol. 17, iss. 1, 2016-01-30.
    cite this publication
    @article{fu_mi_publications1830,
     abstract = {We present CIDANE, a novel framework for genome-based transcript reconstruction and
      quantification from RNA-seq reads. CIDANE assembles transcripts efficiently with significantly
      higher sensitivity and precision than existing tools. Its algorithmic core not only reconstructs
      transcripts ab initio, but also allows the use of the growing annotation of known splice sites,
      transcription start and end sites, or full-length transcripts, which are available for most model
      organisms. CIDANE supports the integrated analysis of RNA-seq and additional gene-boundary data
      and recovers splice junctions that are invisible to other methods. CIDANE is available at
      http://?ccb.?jhu.?edu/?software/?cidane/?.},
     author = {S. Canzar and S. Andreotti and D. Weese and K. Reinert and G. W. Klau},
     journal = {Genome Biology},
     month = {January},
     number = {1},
     publisher = {BioMed Central, Springer Science+Business Media},
     title = {CIDANE: comprehensive isoform discovery and abundance estimation},
     url = {http://publications.imp.fu-berlin.de/1830/},
     volume = {17},
     year = {2016}
    }
  • Marten JĂ€ger, Max Schubach, Tomasz Zemojtel, Knut Reinert, Deanna M. Church, Peter N. Robinson, “Alternate-locus aware variant calling in whole genome sequencing”, vol. 8, iss. 1, 2016-12-13.
    cite this publication
    @article{fu_mi_publications2004,
     abstract = {Background The last two human genome assemblies have extended the previous linear
      golden-path paradigm of the human genome to a graph-like model to better represent regions with a
      high degree of structural variability. The new model offers opportunities to improve the technical
      validity of variant calling in whole-genome sequencing (WGS). Methods We developed an algorithm
      that analyzes the patterns of variant calls in the 178 structurally variable regions of the GRCh38
      genome assembly, and infers whether a given sample is most likely to contain sequences from the
      primary assembly, an alternate locus, or their heterozygous combination at each of these 178
      regions. We investigate 121 in-house WGS datasets that have been aligned to the GRCh37 and GRCh38
      assemblies. Results We show that stretches of sequences that are largely but not entirely
      identical between the primary assembly and an alternate locus can result in multiple variant calls
      against regions of the primary assembly. In WGS analysis, this results in characteristic and
      recognizable patterns of variant calls at positions that we term alignable scaffold-discrepant
      positions (ASDPs). In 121 in-house genomes, on average 51.8{$\pm$}3.8 of the 178 regions were
      found to correspond best to an alternate locus rather than the primary assembly sequence, and
      filtering these genomes with our algorithm led to the identification of 7863 variant calls per
      genome that colocalized with ASDPs. Additionally, we found that 437 of 791 genome-wide association
      study hits located within one of the regions corresponded to ASDPs. Conclusions Our algorithm uses
      the information contained in the 178 structurally variable regions of the GRCh38 genome assembly
      to avoid spurious variant calls in cases where samples contain an alternate locus rather than the
      corresponding segment of the primary assembly. These results suggest the great potential of fully
      incorporating the resources of graph-like genome assemblies into variant calling, but also
      underscore the importance of developing computational resources that will allow a full
      reconstruction of the genotype in personal genomes. Our algorithm is freely available at
      https://github.com/charite/asdpex.},
     author = {Marten J{\"a}ger and Max Schubach and Tomasz Zemojtel and Knut Reinert and Deanna M.
      Church and Peter N. Robinson},
     journal = {Genome Medicine},
     month = {December},
     number = {1},
     publisher = {BioMed Central (Springer Nature)},
     title = {Alternate-locus aware variant calling in whole genome sequencing},
     url = {http://publications.imp.fu-berlin.de/2004/},
     volume = {8},
     year = {2016}
    }
  • Martin ZĂŒhlke, Daniel Riebe, Toralf Beitz, Hans-Gerd Löhmannsröben, Sandro Andreotti, Knut Reinert, Karl Zenichowski, Marc Diener, “High-performance liquid chromatography with electrospray ionization ion mobility spectrometry: Characterization, data management, and applications”, vol. 39, iss. 24, 2016-11-28.
    cite this publication
    @article{fu_mi_publications2128,
     abstract = {The combination of high-performance liquid chromatography and electrospray ionization
      ion mobility spectrometry facilitates the two-dimensional separation of complex mixtures in the
      retention and drift time plane. The ion mobility spectrometer presented here was optimized for
      flow rates customarily used in high-performance liquid chromatography between 100 and 1500
      {\ensuremath{\mu}}L/min. The characterization of the system with respect to such parameters as the
      peak capacity of each time dimension and of the 2D spectrum was carried out based on a separation
      of a pesticide mixture containing 24 substances. While the total ion current chromatogram is
      coarsely resolved, exhibiting coelutions for a number of compounds, all substances can be
      separately detected in the 2D plane due to the orthogonality of the separations in retention and
      drift dimensions. Another major advantage of the ion mobility detector is the identification of
      substances based on their characteristic mobilities. Electrospray ionization allows the detection
      of substances lacking a chromophore. As an example, the separation of a mixture of 18 amino acids
      is presented. A software built upon the free mass spectrometry package OpenMS was developed for
      processing the extensive 2D data. The different processing steps are implemented as separate
      modules which can be arranged in a graphic workflow facilitating automated processing of data.},
     author = {Martin Z{\"u}hlke and Daniel Riebe and Toralf Beitz and Hans-Gerd L{\"o}hmannsr{\"o}ben
      and Sandro Andreotti and Knut Reinert and Karl Zenichowski and Marc Diener},
     journal = {Journal of Separation Science},
     month = {November},
     number = {24},
     pages = {4756--4764},
     publisher = {Wiley},
     title = {High-performance liquid chromatography with electrospray ionization ion mobility
      spectrometry: Characterization, data management, and applications},
     url = {http://publications.imp.fu-berlin.de/2128/},
     volume = {39},
     year = {2016}
    }
  • Hannes L Röst, Timo Sachsenberg, Stephan Aiche, Chris Bielow, Hendrik Weisser, Fabian Aicheler, Sandro Andreotti, Hans-Christian Ehrlich, Petra Gutenbrunner, Erhan Kenar, Xiao Liang, Sven Nahnsen, Lars Nilse, Julianus Pfeuffer, George Rosenberger, Marc Rurik, Uwe Schmitt, Johannes Veit, Mathias Walzer, David Wojnar, Witold E Wolski, Oliver Schilling, Jyoti S Choudhary, Lars Malmström, Ruedi Aebersold, Knut Reinert, Oliver Kohlbacher, “OpenMS: a flexible open-source software platform for mass spectrometry data analysis”, vol. 13, iss. 9, 2016-08-30.
    cite this publication
    @article{fu_mi_publications2129,
     abstract = {High-resolution mass spectrometry (MS) has become an important tool in the life
      sciences, contributing to the diagnosis and understanding of human diseases, elucidating
      biomolecular structural information and characterizing cellular signaling networks. However, the
      rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible
      analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source,
      cross-platform software specifically designed for the flexible and reproducible analysis of
      high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data
      processing tasks through a well-defined application programming interface in C++ and Python and
      through standardized open data formats. OpenMS additionally provides a set of 185 tools and
      ready-made workflows for common mass spectrometric data processing tasks, which enable users to
      perform complex quantitative mass spectrometric analyses with ease.},
     author = {Hannes L R{\"o}st and Timo Sachsenberg and Stephan Aiche and Chris Bielow and Hendrik
      Weisser and Fabian Aicheler and Sandro Andreotti and Hans-Christian Ehrlich and Petra Gutenbrunner
      and Erhan Kenar and Xiao Liang and Sven Nahnsen and Lars Nilse and Julianus Pfeuffer and George
      Rosenberger and Marc Rurik and Uwe Schmitt and Johannes Veit and Mathias Walzer and David Wojnar
      and Witold E Wolski and Oliver Schilling and Jyoti S Choudhary and Lars Malmstr{\"o}m and Ruedi
      Aebersold and Knut Reinert and Oliver Kohlbacher},
     journal = {Nature Methods},
     month = {August},
     number = {9},
     pages = {741--748},
     publisher = {Springer Nature/Macmillan Publishers Limited},
     title = {OpenMS: a flexible open-source software platform for mass spectrometry data analysis},
     url = {http://publications.imp.fu-berlin.de/2129/},
     volume = {13},
     year = {2016}
    }
  • Luis de la Garza, Johannes Veit, Andras Szolek, Marc Röttig, Stephan Aiche, Sandra Gesing, Knut Reinert, Oliver Kohlbacher, “From the desktop to the grid: scalable bioinformatics via workflow conversion”, vol. 17, iss. 1, 2016-03-12.
    cite this publication
    @article{fu_mi_publications2130,
     abstract = {Background Reproducibility is one of the tenets of the scientific method. Scientific
      experiments often comprise complex data flows, selection of adequate parameters, and analysis and
      visualization of intermediate and end results. Breaking down the complexity of such experiments
      into the joint collaboration of small, repeatable, well defined tasks, each with well defined
      inputs, parameters, and outputs, offers the immediate benefit of identifying bottlenecks, pinpoint
      sections which could benefit from parallelization, among others. Workflows rest upon the notion of
      splitting complex work into the joint effort of several manageable tasks. There are several
      engines that give users the ability to design and execute workflows. Each engine was created to
      address certain problems of a specific community, therefore each one has its advantages and
      shortcomings. Furthermore, not all features of all workflow engines are royalty-free {--}an aspect
      that could potentially drive away members of the scientific community. Results We have developed a
      set of tools that enables the scientific community to benefit from workflow interoperability. We
      developed a platform-free structured representation of parameters, inputs, outputs of command-line
      tools in so-called Common Tool Descriptor documents. We have also overcome the shortcomings and
      combined the features of two royalty-free workflow engines with a substantial user community: the
      Konstanz Information Miner, an engine which we see as a formidable workflow editor, and the Grid
      and User Support Environment, a web-based framework able to interact with several high-performance
      computing resources. We have thus created a free and highly accessible way to design workflows on
      a desktop computer and execute them on high-performance computing resources. Conclusions Our work
      will not only reduce time spent on designing scientific workflows, but also make executing
      workflows on remote high-performance computing resources more accessible to technically
      inexperienced users. We strongly believe that our efforts not only decrease the turnaround time to
      obtain scientific results but also have a positive impact on reproducibility, thus elevating the
      quality of obtained scientific results.},
     author = {Luis de la Garza and Johannes Veit and Andras Szolek and Marc R{\"o}ttig and Stephan
      Aiche and Sandra Gesing and Knut Reinert and Oliver Kohlbacher},
     journal = {BMC Bioinformatics},
     month = {March},
     number = {1},
     publisher = {Springer Nature},
     title = {From the desktop to the grid: scalable bioinformatics via workflow conversion},
     url = {http://publications.imp.fu-berlin.de/2130/},
     volume = {17},
     year = {2016}
    }
  • Konstantin Okonechnikov, “High-throughput RNA sequencing: a step forward in transcriptome analysis”, 2016-02-25.
    cite this publication
    @phdthesis{fu_mi_publications2529,
     abstract = {The transcriptome plays an important role in the life of a cell. Detailed analysis of
      the transcriptome enables interpretation of its structure and functionality. High throughput
      sequencing technology significantly enhanced the understanding of transcriptome activity. The
      RNA-sequencing process currently provides the most accurate estimation of gene expression levels.
      Moreover, RNA-seq allows detection of isoform structure and novel RNA types along with
      transcription process details such as strand-specificity and much more. The first chapter of this
      thesis describes the history of transcriptome exploration and effective methods of RNA-seq
      application. Nevertheless, all steps of RNA-seq process can produce a number of biases that
      influence the investigation results. Some typical errors appearing during ligation and
      amplification procedures might be present in any high throughput sequencing experiment, while
      other biases occur only in cDNA synthesis or are specific for transcriptome activity. Quality
      control of sequencing data is important to verify and correct the analysis results. The second
      chapter of this thesis is devoted to the explanation of these issues and introduces a novel tool,
      Qualimap 2. This instrument computes detailed statistics and presents a number of plots based on
      RNA-seq alignment and counts data processing. The generated results enable detection of problems
      that are specific to RNA-seq experiments. Notably, the tool supports analysis of multiple samples
      in various conditions. Qualimap 2 was faithfully compared to other available tools and
      demonstrated superior functionality in multi-sample quality control. Importantly, RNA-seq can be
      applied in a relatively novel research area: detection of chimeric transcripts and fusion genes
      occurring due to genomic rearrangement. Since fusions are related to cancer, their discovery is
      important not only for science, but also allows medical use of RNA-seq. The third chapter is
      devoted to the current status of this approach and illustrates a novel toolkit called InFusion,
      which provides a number of novelties in chimera discovery from RNA- seq data such as detection of
      fusions arising from the combination of a gene and an intronic or intergenic region. Moreover,
      strand-specificity of expressed fusion transcripts can be detected and reported. InFusion was
      compared in detail to a number of other existing tools based on simulated and real datasets and
      demonstrated higher precision and recall. Overall, RNA- sequencing technology goes further and
      more specialized analysis abilities are becoming available. New applications of RNA sequencing and
      future directions of research are discussed in the last chapter.},
     author = {Konstantin Okonechnikov},
     month = {February},
     school = {Freie Universit{\"a}t Berlin},
     title = {High-throughput RNA sequencing: a step forward in transcriptome analysis},
     url = {http://publications.imp.fu-berlin.de/2529/},
     year = {2016}
    }

2015

  • J. Hu, K. Reinert, “LocalAli: An Evolutionary-based Local Alignment Approach to Identify Functionally Conserved Modules in Multiple Networks.”, vol. 30, iss. 1, 2015.
    cite this publication
    @article{fu_mi_publications1457,
     abstract = {MOTIVATION:Sequences and protein interaction data are of significance to understand the
      underlying molecular mechanism of organisms. Local network alignment is one of key systematic ways
      for predicting protein functions, identifying functional modules, and understanding the phylogeny
      from these data. Most of currently existing tools, however, encounter their limitations which are
      mainly concerned with scoring scheme, speed and scalability. Therefore, there are growing demands
      for sophisticated network evolution models and efficient local alignment algorithms. RESULTS:We
      developed a fast and scalable local network alignment tool so-called LocalAli for the
      identification of functionally conserved modules in multiple networks. In this algorithm, we
      firstly proposed a new framework to reconstruct the evolution history of conserved modules based
      on a maximum-parsimony evolutionary model. By relying on this model, LocalAli facilitates
      interpretation of resulting local alignments in terms of conserved modules which have been evolved
      from a common ancestral module through a series of evolutionary events. A meta-heuristic method
      simulated annealing was used to search for the optimal or near-optimal inner nodes (i.e. ancestral
      modules) of the evolutionary tree. To evaluate the performance and the statistical significance,
      LocalAli were tested on a total of 26 real datasets and 1040 randomly generated datasets. The
      results suggest that LocalAli outperforms all existing algorithms in terms of coverage,
      consistency and scalability, meanwhile retains a high precision in the identification of
      functionally coherent subnetworks. AVAILABILITY:The source code and test datasets are freely
      available for download under the GNU GPL v3 license at https://code.google.com/p/localali/.
      CONTACT:jialu.hu@fu-berlin.de or knut.reinert@fu-berlin.de.},
     author = {J. Hu and K. Reinert},
     journal = {Bioinformatics},
     number = {1},
     pages = {363--372},
     publisher = {Oxford University Press},
     title = {LocalAli: An Evolutionary-based Local Alignment Approach to Identify Functionally
      Conserved Modules in Multiple Networks.},
     url = {http://publications.imp.fu-berlin.de/1457/},
     volume = {30},
     year = {2015}
    }
  • Anja Wilmes, Chris Bielow, Christina Ranninger, Patricia Bellwon, Lydia Aschauer, Alice Limonciel, Hubert Chassaigne, Theresa Kristl, Stephan Aiche, Christian G. Huber, Claude Guillou, Philipp Hewitt, Martin O. Leonard, Wolfgang Dekant, Frederic Bois, Paul Jennings, “Mechanism of cisplatin proximal tubule toxicity revealed by integrating transcriptomics, proteomics, metabolomics and biokinetics”, vol. 30, iss. 1, Part A, 2015-12-25.
    cite this publication
    @article{fu_mi_publications1488,
     abstract = {Cisplatin is one of the most widely used chemotherapeutic agents for the treatment of
      solid tumours. The major dose-limiting factor is nephrotoxicity, in particular in the proximal
      tubule. Here, we use an integrated omics approach, including transcriptomics, proteomics and
      metabolomics coupled to biokinetics to identify cell stress response pathways induced by
      cisplatin. The human renal proximal tubular cell line RPTEC/TERT1 was treated with sub-cytotoxic
      concentrations of cisplatin (0.5 and 2{\ensuremath{\mu}}M) in a daily repeat dose treating regime
      for up to 14days. Biokinetic analysis showed that cisplatin was taken up from the basolateral
      compartment, transported to the apical compartment, and accumulated in cells over time. This is in
      line with basolateral uptake of cisplatin via organic cation transporter 2 and bioactivation via
      gamma-glutamyl transpeptidase located on the apical side of proximal tubular cells. Cisplatin
      affected several pathways including, p53 signalling, Nrf2 mediated oxidative stress response,
      mitochondrial processes, mTOR and AMPK signalling. In addition, we identified novel pathways
      changed by cisplatin, including eIF2 signalling, actin nucleation via the ARP/WASP complex and
      regulation of cell polarization. In conclusion, using an integrated omic approach together with
      biokinetics we have identified both novel and established mechanisms of cisplatin toxicity.},
     author = {Anja Wilmes and Chris Bielow and Christina Ranninger and Patricia Bellwon and Lydia
      Aschauer and Alice Limonciel and Hubert Chassaigne and Theresa Kristl and Stephan Aiche and
      Christian G. Huber and Claude Guillou and Philipp Hewitt and Martin O. Leonard and Wolfgang Dekant
      and Frederic Bois and Paul Jennings},
     journal = {Toxicology in Vitro},
     month = {December},
     number = {1, Part A},
     pages = {117--127},
     publisher = {Elsevier B.V.},
     title = {Mechanism of cisplatin proximal tubule toxicity revealed by integrating transcriptomics,
      proteomics, metabolomics and biokinetics},
     url = {http://publications.imp.fu-berlin.de/1488/},
     volume = {30},
     year = {2015}
    }
  • S. Aiche, T. Sachsenberg, E. Kenar, M. Walzer, B. Wiswedel, T. Kristl, M. Boyles, A. Duschl, C. G. Huber, M. R. Berthold, K. Reinert, O. Kohlbacher, “Workflows for automated downstream data analysis and visualization in large-scale computational mass spectrometry”, vol. 15, iss. 8, 2015-04.
    cite this publication
    @article{fu_mi_publications1505,
     abstract = {MS-based proteomics and metabolomics are rapidly evolving research fields driven by the
      development of novel instruments, experimental approaches, and analysis methods. Monolithic
      analysis tools perform well on single tasks but lack the flexibility to cope with the constantly
      changing requirements and experimental setups. Workflow systems, which combine small processing
      tools into complex analysis pipelines, allow custom-tailored and flexible data-processing
      workflows that can be published or shared with collaborators. In this article, we present the
      integration of established tools for computational MS from the open-source software framework
      OpenMS into the workflow engine Konstanz Information Miner (KNIME) for the analysis of large
      datasets and production of high-quality visualizations. We provide example workflows to
      demonstrate combined data processing and visualization for three diverse tasks in computational
      MS: isobaric mass tag based quantitation in complex experimental setups, label-free quantitation
      and identification of metabolites, and quality control for proteomics experiments.},
     author = {S. Aiche and T. Sachsenberg and E. Kenar and M. Walzer and B. Wiswedel and T. Kristl and
      M. Boyles and A. Duschl and C. G. Huber and M. R. Berthold and K. Reinert and O. Kohlbacher},
     journal = {PROTEOMICS},
     month = {April},
     number = {8},
     pages = {1443--1447},
     publisher = {Wiley VCH},
     title = {Workflows for automated downstream data analysis and visualization in large-scale
      computational mass spectrometry},
     url = {http://publications.imp.fu-berlin.de/1505/},
     volume = {15},
     year = {2015}
    }
  • M. Holtgrewe, L. Kuchenbecker, K. Reinert, “Methods for the Detection and Assembly of Novel Sequence in High-Throughput Sequencing Data”, vol. 31, iss. 12, 2015.
    cite this publication
    @article{fu_mi_publications1506,
     abstract = {Motivation: Large insertions of novel sequence are an important type of structural
      variants. Previous studies used traditional de novo assemblers for assembling non-mapping
      high-throughput sequencing (HTS) or capillary reads and then tried to anchor them in the reference
      using paired read information. Results: We present approaches for detecting insertion breakpoints
      and targeted assembly of large insertions from HTS paired data: BASIL and ANISE. On near identity
      repeats that are hard for assemblers, ANISE employs a repeat resolution step. This results in far
      better reconstructions than obtained by the compared methods. On simulated data, we found our
      insert assembler to be competitive with the de novo assemblers ABYSS and SGA while yielding
      already anchored inserted sequence as opposed to unanchored contigs as from ABYSS/SGA. On
      real-world data, we detected novel sequence in a human individual and thoroughly validated the
      assembled sequence. ANISE was found to be superior to the competing tool MindTheGap on both
      simulated and real-world data. Availability and implementation: ANISE and BASIL are available for
      download at http://www.seqan.de/projects/herbarium under a permissive open source license.
      Contact: manuel.holtgrewe@fu-berlin.de or knut.reinert@fu-berlin.de},
     author = {M. Holtgrewe and L. Kuchenbecker and K. Reinert},
     journal = {Bioinformatics},
     number = {12},
     pages = {1904--1912},
     title = {Methods for the Detection and Assembly of Novel Sequence in High-Throughput Sequencing
      Data},
     url = {http://publications.imp.fu-berlin.de/1506/},
     volume = {31},
     year = {2015}
    }
  • K. Reinert, B. Langmead, D. Weese, D.J. Evers, “Alignment of Next-Generation Sequencing Reads”, vol. 16, iss. 1, 2015-05-04.
    cite this publication
    @article{fu_mi_publications1544,
     abstract = {High-throughput DNA sequencing has considerably changed the possibilities for
      conducting biomedical research by measuring billions of short DNA or RNA fragments. A central
      computational problem, and for many applications a first step, consists of determining where the
      fragments came from in the original genome. In this article, we review the main techniques for
      generating the fragments, the main applications, and the main algorithmic ideas for computing a
      solution to the read alignment problem. In addition, we describe pitfalls and difficulties
      connected to determining the correct positions of reads.},
     author = {K. Reinert and B. Langmead and D. Weese and D.J. Evers},
     journal = {Annual Review of Genomics and Human Genetics},
     month = {May},
     number = {1},
     pages = {133--151},
     title = {Alignment of Next-Generation Sequencing Reads},
     url = {http://publications.imp.fu-berlin.de/1544/},
     volume = {16},
     year = {2015}
    }
  • L. Kuchenbecker, M. Nienen, J. Hecht, A. U. Neumann, N. Babel, K. Reinert, P. N. Robinson, “IMSEQ - a fast and error aware approach to immunogenetic sequence analysis”, vol. 31, iss. 18, 2015.
    cite this publication
    @article{fu_mi_publications1551,
     abstract = {Motivation: Recombined T and B cell receptor repertoires are increasingly being studied
      using next generation sequencing (NGS) in order to interrogate the repertoire composition as well
      as changes in the distribution of receptor clones under different physiological and disease
      states. This type of analysis requires efficient and unambiguous clonotype assignment to a large
      number of NGS read sequences, including the identification of the incorporated V and J gene
      segments and the CDR3 sequence. Current tools have deficits with respect to performance, accuracy
      and documentation of their underlying algorithms and usage. Results: We present IMSEQ, a method to
      derive clonotype repertoires from next generation sequencing data with sophisticated routines for
      handling errors stemming from PCR and sequencing artefacts. The application can handle different
      kinds of input data originating from single- or paired-end sequencing in different configurations
      and is generic regarding the species and gene of interest. We have carefully evaluated our method
      with simulated and real world data and show that IMSEQ is superior to other tools with respect to
      its clonotyping as well as standalone error correction and runtime performance. Availability:
      IMSEQ was implemented in C++ using the SeqAn library for efficient sequence analysis. It is freely
      available under the GPLv2 open source license and can be downloaded at www.imtools.org.},
     author = {L. Kuchenbecker and M. Nienen and J. Hecht and A. U. Neumann and N. Babel and K. Reinert
      and P. N. Robinson},
     journal = {Bioinformatics},
     number = {18},
     pages = {2963--2971},
     publisher = {Oxford University Press (online advanced access)},
     title = {IMSEQ - a fast and error aware approach to immunogenetic sequence analysis},
     url = {http://publications.imp.fu-berlin.de/1551/},
     volume = {31},
     year = {2015}
    }
  • L. Schultz, M.-G. Zurich, M. Culot, A. da Costa, C. Landry, P. Bellwon, T. Kristl, K. Hörmann, S. Ruzek, S. Aiche, K. Reinert, C. Bielow, F. Gosselet, R. Cecchelli, C. G. Huber, O. H.-U. Schroeder, A. Gramowski-Voss, D. G. Weiss, A. Bal-Price, “Evaluation of drug-induced neurotoxicity based on metabolomics, proteomics and electrical activity measurements in complementary CNS in vitro models”, vol. 30, iss. 1, 2015-12-25.
    cite this publication
    @article{fu_mi_publications1736,
     abstract = {The present study was performed in an attempt to develop an in vitro integrated testing
      strategy (ITS) to evaluate drug-induced neurotoxicity. A number of endpoints were analyzed using
      two complementary brain cell culture models and an in vitro blood?brain barrier (BBB) model after
      single and repeated exposure treatments with selected drugs that covered the major biological,
      pharmacological and neuro-toxicological responses. Furthermore, four drugs (diazepam, cyclosporine
      A, chlorpromazine and amiodarone) were tested more in depth as representatives of different
      classes of neurotoxicants, inducing toxicity through different pathways of toxicity. The developed
      in vitro BBB model allowed detection of toxic effects at the level of BBB and evaluation of drug
      transport through the barrier for predicting free brain concentrations of the studied drugs. The
      measurement of neuronal electrical activity was found to be a sensitive tool to predict the
      neuroactivity and neurotoxicity of drugs after acute exposure. The histotypic 3D re-aggregating
      brain cell cultures, containing all brain cell types, were found to be well suited for OMICs
      analyses after both acute and long term treatment. The obtained data suggest that an in vitro ITS
      based on the information obtained from BBB studies and combined with metabolomics, proteomics and
      neuronal electrical activity measurements performed in stable in vitro neuronal cell culture
      systems, has high potential to improve current in vitro drug-induced neurotoxicity evaluation.
      Abbreviations: BBB, blood brain barrier; DMSO, dimethylsulfoxide; EC, endothelial cells; DIV, day
      in vitro; IPA, Ingenuity Pathway Analysis; ITS, integrated testing strategy; LY, Lucifer Yellow;
      MEA, micro-electrode array; RH, Ringer HEPES medium; SPSS, Statistical Package for the Social
      Sciences},
     author = {L. Schultz and M.-G. Zurich and M. Culot and A. da Costa and C. Landry and P. Bellwon and
      T. Kristl and K. H{\"o}rmann and S. Ruzek and S. Aiche and K. Reinert and C. Bielow and F.
      Gosselet and R. Cecchelli and C. G. Huber and O. H.-U. Schroeder and A. Gramowski-Voss and D. G.
      Weiss and A. Bal-Price},
     journal = {Toxicology in Vitro},
     keywords = {In vitro blood brain barrier; MEA; Neuronal network culture; OMICs; Drug development;
      3D brain culture},
     month = {December},
     note = {Online publication: May 2015},
     number = {1},
     pages = {138--165},
     publisher = {Elsevier B.V.},
     title = {Evaluation of drug-induced neurotoxicity based on metabolomics, proteomics and electrical
      activity measurements in complementary CNS in vitro models},
     url = {http://publications.imp.fu-berlin.de/1736/},
     volume = {30},
     year = {2015}
    }
  • Enrico Siragusa, “Approximate string matching for high-throughput sequencing”, p. 127, 2015-07-23.
    cite this publication
    @phdthesis{fu_mi_publications2507,
     abstract = {Over the past years, high-throughput sequencing (HTS) has become an invaluable method
      of investigation in molecular and medical biology. HTS technologies allow to sequence cheaply and
      rapidly an individual?s DNA sample under the form of billions of short DNA reads. The ability to
      assess the content of a DNA sample at base-level resolution opens the way to a myriad of
      applications, including individual genotyping and assessment of large structural variations,
      measurement of gene expression levels and characterization of epigenetic features. Nonetheless,
      the quantity and quality of data produced by HTS instruments call for computationally efficient
      and accurate analysis methods. In this thesis, I present novel methods for the mapping of
      high-throughput sequencing DNA reads, based on state of the art approximate string matching
      algorithms and data structures. Read mapping is a fundamental step of any HTS data analysis
      pipeline in resequencing projects, where DNA reads are reassembled by aligning them back to a
      previously known reference genome. The ingenuity of approximate string matching methods is crucial
      to design efficient and accurate read mapping tools. In the first part of this thesis, I cover
      practical indexing and filtering methods for exact and approximate string matching. I present
      state of the art algorithms and data structures, give their pseudocode and discuss their
      implementation. Furthermore, I provide all implementations within SeqAn, the generic C++ template
      library for sequence analysis, which is freely available under http://www.seqan.de/. Subsequently,
      I experimentally evaluate all implemented methods, with the aim of guiding the engineering of new
      sequence alignment software. To the best of my knowledge, this is the first study providing a
      comprehensive exposition, implementation and evaluation of such methods. In the second part of
      this thesis, I turn to the engineering and evaluation of read mapping tools. First, I present a
      novel method to find all mapping locations per read within a user- defined error rate; this method
      is published in the peer-reviewed journal Nucleic Acids Research and packaged in a open source
      tool nicknamed Masai. Afterwards, I generalize this method to quickly report all co-optimal or
      suboptimal mapping locations per read within a user-defined error rate; this method, packaged in a
      tool called Yara, provides a more practical, yet sound solution to the read mapping problem.
      Extensive evaluations, both on simulated and real datasets, show that Yara has better speed and
      accuracy than de-facto standard read mapping tools.},
     author = {Enrico Siragusa},
     month = {July},
     school = {Freie Universit{\"a}t Berlin},
     title = {Approximate string matching for high-throughput sequencing},
     url = {http://publications.imp.fu-berlin.de/2507/},
     year = {2015}
    }
  • Jialu Hu, “Algorithms to Identify Functional Orthologs And Functional Modules from High- Throughput Data”, 2015-01-07.
    cite this publication
    @phdthesis{fu_mi_publications2521,
     abstract = {Many studies in the last decade suggest that the biological network topology
      supplementing the genome is another important source of biological information for understanding
      the fundamental principle of life processes. A typical approach aiming to gain insights from the
      network information is network alignment. It provides a promising framework to understand the
      organization, function and evolution of molecular networks. However, current algorithms encounter
      their bottlenecks in terms of scalability, speed and so forth when applied to analyze multiple
      networks. Hence, it is desired to develop novel, efficient strategies to cope with the rapidly
      growing data in this particular field. In this thesis, we present two new network alignment
      algorithms, LocalAli and NetCoffee, and their applications in the analysis of biological data.
      Both of the two algorithms focus on the problem of multiple network alignment, but they run into
      different directions: local alignment and global alignment. LocalAli is an evolutionary-based
      local alignment approach that aims to identify functionally conserved modules from multiple
      biological networks. In this algorithm, a computational framework is firstly proposed to
      reconstruct the evolution history of functionally conserved modules. NetCoffee is a global
      alignment approach with a goal to detect function-oriented ortholog groups from multiple
      biological networks. The two algorithms have been applied to several real-world datasets. The
      results show that both Localali and Netcoffee provide substantial improvements to current
      algorithms in terms of several criteria such as scalability, coverage and consistency. All the
      test datasets, binaries and source code used for this thesis are freely available at
      https://code.google.com/p/localali/ and https://code.google.com/p/netcoffee/.},
     author = {Jialu Hu},
     month = {January},
     school = {Freie Universit{\"a}t Berlin},
     title = {Algorithms to Identify Functional Orthologs And Functional Modules from High- Throughput
      Data},
     url = {http://publications.imp.fu-berlin.de/2521/},
     year = {2015}
    }
  • Manuel Holtgrewe, “Engineering Algorithms for Personal Genome Pipelines”, 2015-11-11.
    cite this publication
    @phdthesis{fu_mi_publications2530,
     abstract = {Recent technical advances in high-throughput sequencing technologies and their
      commercial availability at low costs have paved the way for revolutionary opportunities in the
      life sciences. One milestone was reaching the \$1000 genome, allowing to determine the genetic
      makeup of hundreds of human individuals within a week for less than \$1000 each. This ongoing
      revolution of the life sciences creates new challenges for the software and algorithms that are
      processing this data. In my thesis, I consider a typical software pipeline for determining the
      genome of a human individual. For the preprocessing pipeline step, I describe a method for error
      correction and consider the comparison of such methods. For the read mapping step, I provide a
      formal definition of read mapping and I present a software package implementing a benchmark for
      read mapping, based on my formal definition. I then describe the implementation, parallelisation,
      and engineering of a fully sensitive read mapper and evaluate its performance. For the variant
      calling step, I present a method for the prediction of insertion breakpoints and the assembly of
      large insertions. Of course, such a pipeline is not limited to the processing of human data but it
      is also applicable to data from other mammals or organisms with smaller and less complex genomes.
      The presented work is available as an efficient open source C++ implementation, either as parts of
      the SeqAn library or as programs using SeqAn.},
     author = {Manuel Holtgrewe},
     month = {November},
     school = {Freie Universit{\"a}t Berlin},
     title = {Engineering Algorithms for Personal Genome Pipelines},
     url = {http://publications.imp.fu-berlin.de/2530/},
     year = {2015}
    }
  • Sandro Andreotti, “Linear Programming and Integer Linear Programming in Bioinformatics”, 2015-02-06.
    cite this publication
    @phdthesis{fu_mi_publications2531,
     abstract = {A wide range of important problems related to bioinformatics and computational biology
      are optimization problems asking for a solution that minimizes or maximizes a certain objective
      function. Often, these problems are combinatorial optimization problems that can be formulated as
      integer linear programs. While for some of these problems polynomial time algorithms are known,
      for many other problems it is unlikely that such algorithms exist. However, much work has been
      dedicated to develop algorithms that are capable of solving many interesting integer linear
      programming problems on real live instances with acceptable memory and running time requirements.
      These algorithms are implemented in a variety of free or commercial solver software packages. In
      situations where the performance of general purpose solvers is insufficient, often problem
      specific integer linear programming techniques can be applied that take advantage of knowledge
      about the particular structure of the integer linear programming formulation to solve the problem
      in a much more time- or space-efficient way. In this thesis we present our algorithmic approaches
      to three relevant bioinformatic problems, each involving certain linear programming and integer
      linear programming techniques. The first problem is the de novo peptide sequencing problem, which
      consists in identifying a peptide's sequence solely from its tandem mass spectrum without any
      additional information stored in genome databases or protein databases. This problem can be
      formulated as a graph theoretical problem asking for the computation of a longest antisymmetric
      path in a directed acyclic graph. The particular structure of the associated integer linear
      programming formulation facilitates the application of a technique called Lagrangian relaxation,
      which yields an algorithm that outperforms state-of-the-art commercial integer linear programming
      solvers by orders of magnitude. The second problem is the isoform inference and abundance
      estimation problem from RNA-Seq data. This problem consists in predicting a set of expressed RNA
      isoforms, i.e., full length RNA transcripts corresponding to alternative splice variants, together
      with an estimate of their individual expression levels. We apply a linear programming technique
      called delayed column generation, which allows us to increase the search space without explicitly
      enumerating the potentially huge set of candidate isoforms. As a consequence, our approach allows
      for the identification of isoforms that otherwise could not be recovered due to incomplete read
      coverage. A central component of our delayed column generation algorithm is an integer linear
      programming formulation. The third problem is the duplication-loss alignment problem, which asks
      for a labeled alignment of two genome sequences that implies the minimal number of loss and
      duplication events in the evolutionary history from an unknown nearest common ancestor. In a
      labeled alignment, every unaligned gene must be labeled either as a loss or as the product of a
      duplication event. Once an optimal labeled alignment has been computed, a common ancestor genome
      with minimal implied evolutionary operations can be derived in a straight forward way. In our
      approach we identified problem specific cutting planes and developed efficient separation
      algorithms to obtain a branch and cut algorithm that is several orders of magnitude faster than
      existing approaches based on integer linear programming.},
     author = {Sandro Andreotti},
     month = {February},
     school = {Freie Universit{\"a}t Berlin},
     title = {Linear Programming and Integer Linear Programming in Bioinformatics},
     url = {http://publications.imp.fu-berlin.de/2531/},
     year = {2015}
    }
  • Xintian Arthur You, “Tailored Analysis in Studying Transcriptome Landscape”, 2015-12-22.
    cite this publication
    @phdthesis{fu_mi_publications2532,
     abstract = {The knowledge of the transcriptome landscape is crucial in molecular biology, and
      increasingly more important for disease diagnosis and treatments. Broadly speaking, three layers
      contribute to the importance of the transcriptome landscape. First, the profile of all isoforms of
      protein-coding genes determines the development path of cells and organisms. Second, the profile
      of regulatory elements modulates the activity of protein-coding genes. Third, the interplay of
      protein-coding genes and regulatory elements shapes the dynamic property of transcriptome
      landscape. Identifying the players in the regulatory network is the first step for
      reverse-engineering molecular biology. In this thesis, I present four tailored analyses on
      projects belonging to the first two layers. First, a hybrid assembly pipeline is developed for
      identification of transcriptome independent of genomic sequences. By combining two complementary
      sequencing technologies in conjunction with efficient cDNA normalization, a high quality
      transcriptome can be characterized. It out- performs other assembly tools that focus on one type
      of input data, and the results are experimentally validated. Second, an analysis framework is
      developed to characterize full-length transcripts. By tailoring tools for long read-length
      sequencing technology, transcriptome landscape could be examined with greater detail. Moreover,
      the association of different RNA processing events could be experimentally measured. The
      application on fly Dscam gene transcripts resolved the independent splicing hypothesis and calls
      for re- examination of previous experiments. The application on rat brain greatly enhanced the
      transcriptome annotation, which is crucial for the neuroscience community that use rat as a model
      organism. Third, a de novo microRNA prediction tools is presented. By designing sequencing
      experiments that capture snapshots of miRNA biogenesis process, not only mature and precursor
      miRNAs could be identified, but also the information on miRNA processing and modification could be
      learnt. Proof- of-principle experiments on well-studies organism like mouse and C. elegans
      demonstrate the efficacy and application potential of this method. Finally, a customized pipeline
      is developed for profiling and characterizing circRNAs. By examining potential splicing junctions
      based on local alignments, circRNAs can be identified from the otherwise neglected RNA- Seq data.
      Tens of thousands of circRNAs are identified and quantified in mouse, rat and fly. Further
      experiments demonstrate that circRNAs are enriched in brain synapses and participate in brain
      development and neuronal homeostatic plasticity. In summary, this thesis presents four tailored
      analyses on different aspects of transcriptome landscape. The methods can be used in conjunction
      towards an integrated understanding of molecular biology and medicine.},
     author = {Xintian Arthur You},
     month = {December},
     school = {Freie Universit{\"a}t Berlin},
     title = {Tailored Analysis in Studying Transcriptome Landscape},
     url = {http://publications.imp.fu-berlin.de/2532/},
     year = {2015}
    }
  • Britta Weber, “Reconstruction of Microtubule Centerlines from Electron Tomograms”, 2015-12-21.
    cite this publication
    @phdthesis{fu_mi_publications2544,
     abstract = {The organization of the mitotic spindle, a structure that separates the chromosomes
      during cell division, is an active research topic in molecular cell biology. It is composed of
      microtubules, elongated tubular macromolecules with a diameter of 25 nm. The only volumetric
      imaging technique that is available to a wide community and provides the required resolution to
      capture details about microtubules is electron tomography. However, the automatic detection of
      microtubules in electron tomograms is a difficult task due to the low contrast of the data.
      Furthermore, thick samples have to be cut into 300 nm thin sections before electron tomography can
      be applied. Software for automatically segmentation and stitching of the microtubules are not
      available and therefore these tasks have to be performed manually. Unfortunately, manual
      segmentation is time consuming for large samples and manual stitching of the tomograms is often
      infeasible due to the lack of prominent features for registration. Conclusions drawn from electron
      tomographic data is currently mostly based on either small samples containing few microtubules or
      single sections of complex structures. Consequently, simple properties, such as the length of
      microtubules in the spindle or their number, are still unknown for most model organisms. In this
      thesis, we present methods for 1) an automatic segmentation of microtubule centerlines in electron
      tomograms, and 2) an automatic stitching of the lines extracted from serial sections. For the
      centerline segmentation, we use 3D template matching and exploit knowledge about shape of
      microtubules and microscopy artifacts to design the templates. For the registration of the lines,
      we present a way to model the orientation of lines as a mixture of Fisher-Mises distributions
      where we estimate transformation parameters with the expectation maximization algorithm. The final
      line matching problem is formulated in terms of a probabilistic graphical model. To find the
      correct correspondences of line ends, we use belief propagation. We handle the poor convergence
      properties of this algorithm by detecting ambiguous and conflicting assignments of lines
      automatically. An expert can then influence the final output of the algorithm by solving conflicts
      manually. A detailed error analysis on true biological data and assessment of the reliability of
      the results is the prerequisite for analyzing the resulting line representations of the
      microtubules. To this end, the developed workflow for segmenting and stitching of microtubule
      centerlines is evaluated on plasticembedded samples of C. elegans early embryos and of spindles
      from X. laevis egg extracts. Our results suggest that the output of the presented algorithms
      together with little manual correction is of sufficient quality to allow a detailed analysis of
      dense microtubule networks. Finally, we exemplarily show results for the centrosome of a C.
      elegans mitotic spindle.},
     author = {Britta Weber},
     month = {December},
     school = {Freie Universit{\"a}t Berlin},
     title = {Reconstruction of Microtubule Centerlines from Electron Tomograms},
     url = {http://publications.imp.fu-berlin.de/2544/},
     year = {2015}
    }

2014

  • J. Hu, B. Kehr, K. Reinert, “NetCoffee: a fast and accurate global alignment approach to identify functionally conserved proteins in multiple networks”, vol. 30, iss. 4, 2014-02-15.
    cite this publication
    @article{fu_mi_publications1399,
     abstract = {Motivation: Owing to recent advancements in high-throughput technologies,
      protein?protein interaction networks of more and more species become available in public
      databases. The question of how to identify functionally conserved proteins across species attracts
      a lot of attention in computational biology. Network alignments provide a systematic way to solve
      this problem. However, most existing alignment tools encounter limitations in tackling this
      problem. Therefore, the demand for faster and more efficient alignment tools is growing. Results:
      We present a fast and accurate algorithm, NetCoffee, which allows to find a global alignment of
      multiple protein?protein interaction networks. NetCoffee searches for a global alignment by
      maximizing a target function using simulated annealing on a set of weighted bipartite graphs that
      are constructed using a triplet approach similar to T-Coffee. To assess its performance, NetCoffee
      was applied to four real datasets. Our results suggest that NetCoffee remedies several limitations
      of previous algorithms, outperforms all existing alignment tools in terms of speed and
      nevertheless identifies biologically meaningful alignments. Availability: The source code and data
      are freely available for download under the GNU GPL v3 license at
      https://code.google.com/p/netcoffee/.},
     author = {J. Hu and B. Kehr and K. Reinert},
     journal = {Bioinformatics},
     month = {February},
     number = {4},
     pages = {540--548},
     publisher = {Oxford University Press},
     title = {NetCoffee: a fast and accurate global alignment approach to identify functionally
      conserved proteins in multiple networks},
     url = {http://publications.imp.fu-berlin.de/1399/},
     volume = {30},
     year = {2014}
    }
  • S. Wandelt, D. Deng, S. Gerdjikov, S. Mishra, P. Mitankin, M. Patil, E. Siragusa, A. Tiskin, W. Wang, J. Wang, U. Leser, “State-of-the-art in String Similarity Search and Join”, vol. 43, iss. 1, 2014-03.
    cite this publication
    @article{fu_mi_publications1401,
     author = {S. Wandelt and D. Deng and S. Gerdjikov and S. Mishra and P. Mitankin and M. Patil and E.
      Siragusa and A. Tiskin and W. Wang and J. Wang and U. Leser},
     journal = {SIGMOD Record},
     month = {March},
     number = {1},
     title = {State-of-the-art in String Similarity Search and Join},
     url = {http://publications.imp.fu-berlin.de/1401/},
     volume = {43},
     year = {2014}
    }
  • B. Kehr, K. Trappe, M. Holtgrewe, K. Reinert, “Genome alignment with graph data structures: a comparison”, vol. 15, 2014-04-09.
    cite this publication
    @article{fu_mi_publications1437,
     abstract = {Background Recent advances in rapid, low-cost sequencing have opened up the opportunity
      to study complete genome sequences. The computational approach of multiple genome alignment allows
      investigation of evolutionarily related genomes in an integrated fashion, providing a basis for
      downstream analyses such as rearrangement studies and phylogenetic inference. Graphs have proven
      to be a powerful tool for coping with the complexity of genome-scale sequence alignments. The
      potential of graphs to intuitively represent all aspects of genome alignments led to the
      development of graph-based approaches for genome alignment. These approaches construct a graph
      from a set of local alignments, and derive a genome alignment through identification and removal
      of graph substructures that indicate errors in the alignment. Results We compare the structures of
      commonly used graphs in terms of their abilities to represent alignment information. We describe
      how the graphs can be transformed into each other, and identify and classify graph substructures
      common to one or more graphs. Based on previous approaches, we compile a list of modifications
      that remove these substructures. Conclusion We show that crucial pieces of alignment information,
      associated with inversions and duplications, are not visible in the structure of all graphs. If we
      neglect vertex or edge labels, the graphs differ in their information content. Still, many ideas
      are shared among all graph-based approaches. Based on these findings, we outline a conceptual
      framework for graph-based genome alignment that can assist in the development of future genome
      alignment tools.},
     author = {B. Kehr and K. Trappe and M. Holtgrewe and K. Reinert},
     journal = {BMC Bioinformatics},
     month = {April},
     publisher = {BioMed Central},
     title = {Genome alignment with graph data structures: a comparison},
     url = {http://publications.imp.fu-berlin.de/1437/},
     volume = {15},
     year = {2014}
    }
  • R. Rahn, D. Weese, K. Reinert, “Journaled string tree--a scalable data structure for analyzing thousands of similar genomes on your laptop”, 2014-07-15.
    cite this publication
    @article{fu_mi_publications1448,
     abstract = {Motivation: Next-generation sequencing (NGS) has revolutionized biomedical research in
      the past decade and led to a continuous stream of developments in bioinformatics, addressing the
      need for fast and space-efficient solutions for analyzing NGS data. Often researchers need to
      analyze a set of genomic sequences that stem from closely related species or are indeed
      individuals of the same species. Hence, the analyzed sequences are similar. For analyses where
      local changes in the examined sequence induce only local changes in the results, it is obviously
      desirable to examine identical or similar regions not repeatedly. Results: In this work, we
      provide a datatype that exploits data parallelism inherent in a set of similar sequences by
      analyzing shared regions only once. In real-world experiments, we show that algorithms that
      otherwise would scan each reference sequentially can be speeded up by a factor of 115.
      Availability: The data structure and associated tools are publicly available at
      http://www.seqan.de/projects/jst and are part of SeqAn, the C++ template library for sequence
      analysis. Contact: rene.rahn@fu-berlin.de},
     author = {R. Rahn and D. Weese and K. Reinert},
     journal = {Bioinformatics},
     month = {July},
     title = {Journaled string tree--a scalable data structure for analyzing thousands of similar
      genomes on your laptop},
     url = {http://publications.imp.fu-berlin.de/1448/},
     year = {2014}
    }
  • M. Walzer, L. E. Pernas, S. Nasso, W. Bittremieux, S. Nahnsen, P. Kelchtermans, P. Pichler, H. W. P. van den Toorn, A. Staes, J. Vandenbussche, M. Mazanek, T. Taus, R. A. Scheltema, C. D. Kelstrup, L. Gatto, B. van Breukelen, S. Aiche, D. Valkenborg, K. Laukens, K. S. Lilley, J. V. Olsen, A. J. R. Heck, K. Mechtler, R. Aebersold, K. Gevaert, J. A. Vizcaino, H. Hermjakob, O. Kohlbacher, L. Martens, “qcML: An Exchange Format for Quality Control Metrics from Mass Spectrometry Experiments”, vol. 13, iss. 8, 2014-08-01.
    cite this publication
    @article{fu_mi_publications1449,
     abstract = {Quality control is increasingly recognized as a crucial aspect of mass spectrometry
      based proteomics. Several recent papers discuss relevant parameters for quality control and
      present applications to extract these from the instrumental raw data. What has been missing,
      however, is a standard data exchange format for reporting these performance metrics. We therefore
      developed the qcML format, an XML-based standard that follows the design principles of the related
      mzML, mzIdentML, mzQuantML, and TraML standards from the HUPO-PSI (Proteomics Standards
      Initiative). In addition to the XML format, we also provide tools for the calculation of a wide
      range of quality metrics as well as a database format and interconversion tools, so that existing
      LIMS systems can easily add relational storage of the quality control data to their existing
      schema. We here describe the qcML specification, along with possible use cases and an illustrative
      example of the subsequent analysis possibilities. All information about qcML is available at
      http://code.google.com/p/qcml. Molecular \& Cellular Proteomics 13: 10.1074/mcp.M113.035907,
      1905?1913, 2014.},
     author = {M. Walzer and L. E. Pernas and S. Nasso and W. Bittremieux and S. Nahnsen and P.
      Kelchtermans and P. Pichler and H. W. P. van den Toorn and A. Staes and J. Vandenbussche and M.
      Mazanek and T. Taus and R. A. Scheltema and C. D. Kelstrup and L. Gatto and B. van Breukelen and
      S. Aiche and D. Valkenborg and K. Laukens and K. S. Lilley and J. V. Olsen and A. J. R. Heck and
      K. Mechtler and R. Aebersold and K. Gevaert and J. A. Vizcaino and H. Hermjakob and O. Kohlbacher
      and L. Martens},
     journal = {Molecular \& Cellular Proteomics},
     month = {August},
     number = {8},
     pages = {1905--1913},
     title = {qcML: An Exchange Format for Quality Control Metrics from Mass Spectrometry Experiments},
     url = {http://publications.imp.fu-berlin.de/1449/},
     volume = {13},
     year = {2014}
    }
  • M. H. Schulz, D. Weese, M. Holtgrewe, V. Dimitrova, S. Niu, K. Reinert, H. Richard, “Fiona: a parallel and automatic strategy for read error correction”, vol. 30, iss. 17, 2014.
    cite this publication
    @article{fu_mi_publications1451,
     abstract = {Motivation: Automatic error correction of high-throughput sequencing data can have a
      dramatic impact on the amount of usable base pairs and their quality. It has been shown that the
      performance of tasks such as de novo genome assembly and SNP calling can be dramatically improved
      after read error correction. While a large number of methods specialized for correcting
      substitution errors as found in Illumina data exist, few methods for the correction of indel
      errors, common to technologies like 454 or Ion Torrent, have been proposed.Results: We present
      Fiona, a new stand-alone read error{\^a}??correction method. Fiona provides a new statistical
      approach for sequencing error detection and optimal error correction and estimates its parameters
      automatically. Fiona is able to correct substitution, insertion and deletion errors and can be
      applied to any sequencing technology. It uses an efficient implementation of the partial suffix
      array to detect read overlaps with different seed lengths in parallel. We tested Fiona on several
      real datasets from a variety of organisms with different read lengths and compared its performance
      with state-of-the-art methods. Fiona shows a constantly higher correction accuracy over a broad
      range of datasets from 454 and Ion Torrent sequencers, without compromise in speed.Conclusion:
      Fiona is an accurate parameter-free read error{\^a}??correction method that can be run on
      inexpensive hardware and can make use of multicore parallelization whenever available. Fiona was
      implemented using the SeqAn library for sequence analysis and is publicly available for download
      at http://www.seqan.de/projects/fiona.Contact: mschulz@mmci.uni-saarland.de or
      hugues.richard@upmc.frSupplementary information: Supplementary data are available at
      Bioinformatics online.},
     author = {M. H. Schulz and D. Weese and M. Holtgrewe and V. Dimitrova and S. Niu and K. Reinert and
      H. Richard},
     journal = {Bioinformatics},
     number = {17},
     pages = {i356--i363},
     title = {Fiona: a parallel and automatic strategy for read error correction},
     url = {http://publications.imp.fu-berlin.de/1451/},
     volume = {30},
     year = {2014}
    }
  • H. Hauswedell, J. Singer, K. Reinert, “Lambda: the local aligner for massive biological data”, vol. 30, iss. 17, 2014-09.
    cite this publication
    @article{fu_mi_publications1453,
     abstract = {MOTIVATION:Next-generation sequencing technologies produce unprecedented amounts of
      data, leading to completely new research fields. One of these is metagenomics, the study of
      large-size DNA samples containing a multitude of diverse organisms. A key problem in metagenomics
      is to functionally and taxonomically classify the sequenced DNA, to which end the well-known BLAST
      program is usually used. But BLAST has dramatic resource requirements at metagenomic scales of
      data, imposing a high financial or technical burden on the researcher. Multiple attempts have been
      made to overcome these limitations and present a viable alternative to BLAST.RESULTS:In this work
      we present Lambda, our own alternative for BLAST in the context of sequence classification. In our
      tests, Lambda often outperforms the best tools at reproducing BLAST's results and is the fastest
      compared with the current state of the art at comparable levels of sensitivity. AVAILABILITY AND
      IMPLEMENTATION:Lambda was implemented in the SeqAn open-source C++ library for sequence analysis
      and is publicly available for download at http://www.seqan.de/projects/lambda.
      CONTACT:hannes.hauswedell@fu-berlin.de SUPPLEMENTARY INFORMATION:Supplementary data are available
      at Bioinformatics online.},
     author = {H. Hauswedell and J. Singer and K. Reinert},
     journal = {Bioinformatics (Oxford, England)},
     month = {September},
     number = {17},
     pages = {i349--i355},
     publisher = {Oxford University Press},
     title = {Lambda: the local aligner for massive biological data},
     url = {http://publications.imp.fu-berlin.de/1453/},
     volume = {30},
     year = {2014}
    }
  • K. Trappe, A.-K. Emde, H.-C. Ehrlich, K. Reinert, “Gustaf: Detecting and correctly classifying SVs in the NGS twilight zone”, vol. 30, iss. 24, 2014-07-14.
    cite this publication
    @article{fu_mi_publications1455,
     abstract = {MOTIVATION: The landscape of structural variation (SV) including complex duplication
      and translocation patterns is far from resolved. SV detection tools usually exhibit low agreement,
      are often geared toward certain types or size ranges of variation and struggle to correctly
      classify the type and exact size of SVs. RESULTS: We present Gustaf (Generic mUlti-SpliT Alignment
      Finder), a sound generic multi-split SV detection tool that detects and classifies deletions,
      inversions, dispersed duplications and translocations of {\ensuremath{<}}span
      class='mathrm'{\ensuremath{>}}ge{\ensuremath{<}}/span{\ensuremath{>}}30 bp. Our approach is based
      on a generic multi-split alignment strategy that can identify SV breakpoints with base pair
      resolution. We show that Gustaf correctly identifies SVs, especially in the range from 30 to 100
      bp, which we call the next-generation sequencing (NGS) twilight zone of SVs, as well as larger SVs
      \&gt;500 bp. Gustaf performs better than similar tools in our benchmark and is furthermore able to
      correctly identify size and location of dispersed duplications and translocations, which otherwise
      might be wrongly classified, for example, as large deletions. Availability and implementation:
      Project information, paper benchmark and source code are available via
      http://www.seqan.de/projects/gustaf/. CONTACT:kathrin.trappe@fu-berlin.de.},
     author = {K. Trappe and A.-K. Emde and H.-C. Ehrlich and K. Reinert},
     journal = {Bioinformatics},
     month = {July},
     number = {24},
     pages = {3484--3490},
     publisher = {Oxford University Press},
     title = {Gustaf: Detecting and correctly classifying SVs in the NGS twilight zone},
     url = {http://publications.imp.fu-berlin.de/1455/},
     volume = {30},
     year = {2014}
    }
  • V. Neu, C. Bielow, K. Reinert, C. G. Huber, “Ultrahigh-performance liquid chromatography-ultraviolet absorbance detection-high-resolution-mass spectrometry combined with automated data processing for studying the kinetics of oxidative thermal degradation of thyroxine in the solid state”, vol. 1371, 2014-12.
    cite this publication
    @article{fu_mi_publications1463,
     abstract = {Received 29 June 2014 Received in revised form 29 September 2014 Accepted 24 October
      2014 Available online 30 October 2014 Keywords: Thyroxine Ultrahigh-performance liquid
      chromatography Electrospray ionization Orbitrap mass spectrometry Kinetics Drug degradation
      Bioinformatics 1. Introduction Levothyroxine (T4) is a well-known and widely used drug for the
      treatment of hypothyroidism. The therapy is usually based on substitution of the natural hormone
      by a long-term treatment with synthetic levothyroxine [1]. It is a narrow therapeutic index drug,
      for which individual dosage levels of patients need to be established over several weeks.
      Consequently, products differing in content of levothyroxine due to compound instability or
      problems in formu- lation can lead to wrong medication and potentially cause severe health
      problems [2,3]. ? Corresponding author. Tel.:+43 0 662 8044 5704; fax: +43 0 662 8044 5751. E-mail
      addresses: volker.a.neu@basf.com (V. Neu), chris.bielow@fu-berlin.de (C. Bielow),
      reinert@inf.fu-berlin.de (K. Reinert), c.huber@sbg.ac.at (C.G. Huber).
      http://dx.doi.org/10.1016/j.chroma.2014.10.071 0021-9673/{\copyright} 2014 Elsevier B.V. All
      rights reserved. abstract Levothyroxine as active pharmaceutical ingredient of formulations used
      for the treatment of hypothy- roidism is distributed worldwide and taken by millions of people. An
      important issue in terms of compound stability is its capability to react with ambient oxygen,
      especially in case of long term com- pound storage at elevated temperature. In this study we
      demonstrate that ultrahigh-performance liquid chromatography coupled to UV spectrometry and
      high-resolution mass spectrometry (UHPLC-UV-HRMS) represent very useful approaches to investigate
      the influence of ambient oxygen on the degradation kinet- ics of levothyroxine in the solid state
      at enhanced degradation conditions. Moreover, the impurity pattern of oxidative degradation of
      levothyroxine is elucidated and classified with respect to degradation kinetics at different
      oxygen levels. Kinetic analysis of thyroxine bulk material at 100 ? C reveals bi-phasic degra-
      dation kinetics with a distinct change in degradation phases dependent on the availability of
      oxygen. The results clearly show that contact of the bulk material to ambient oxygen is a key
      factor for fast compound degradation. Furthermore, the combination of time-resolved HRMS data and
      automated data processing is shown to allow insights into the kinetics and mechanism of impurity
      formation on individual com- pound basis. By comparing degradation profiles, four main classes of
      profiles linked to reaction pathways of thyroxine degradation were identifiable. Finally, we show
      the capability of automated data process- ing for the matching of different stressing conditions,
      in order to extract information about mechanistic similarities. As a result, degradation kinetics
      is influenced by factors like availability of oxygen, stressing time, or stressing temperature,
      while the degradation mechanisms appear to be conserved.},
     author = {V. Neu and C. Bielow and K. Reinert and C. G. Huber},
     journal = {Journal of chromatography A},
     month = {December},
     pages = {196--203},
     title = {Ultrahigh-performance liquid chromatography-ultraviolet absorbance
      detection-high-resolution-mass spectrometry combined with automated data processing for studying
      the kinetics of oxidative thermal degradation of thyroxine in the solid state},
     url = {http://publications.imp.fu-berlin.de/1463/},
     volume = {1371},
     year = {2014}
    }
  • Birte Kehr, “Contributions to computing and modeling multiple whole-genome alignments”, 2014-06-11.
    cite this publication
    @phdthesis{fu_mi_publications2525,
     abstract = {Recent advances in sequencing technologies have opened up the opportunity to study
      whole genomes at the nucleotide level. Similarities in the nucleotide sequences of genomes provide
      new insights in the relationships of organisms and species. Multiple whole-genome alignments
      represent these similarities, however their computation is challenging. In contrast to approaches
      for other sequence alignment problems, genome alignment methods have to deal with very long
      sequences and with non-colinearity of similarities. This thesis makes three contributions to the
      development of multiple whole-genome alignment methods. The prevailing strategy of such methods is
      to combine a set of local alignments to a global genome alignment. This thesis suggests an
      efficient and fully sensitive local alignment approach, compares graph data structures for
      representing genome alignments, and describes hidden rearrangement breakpoints that become visible
      only in the comparison of more than two genomes. All three contributions provide potential for
      significant improvements to the computation or modeling of genome alignments. In a comparison to
      other local alignment approaches, the new local aligner is the fastest of three fully sensitive
      ones and competitive with seed-and-extend approaches despite having full sensitivity. The
      assessment of graph data structures describes for the first time all graphs using the same
      terminology, and demonstrates how the graph structures differ in their information content.
      Finally, an analysis of breakpoints in simulated genome alignments suggests that hidden
      breakpoints are abundant and relevant for measuring the accuracy of genome alignments. In summary,
      the three contributions provide a promising basis for future genome alignment methods.},
     author = {Birte Kehr},
     month = {June},
     school = {Freie Universit{\"a}t Berlin},
     title = {Contributions to computing and modeling multiple whole-genome alignments},
     url = {http://publications.imp.fu-berlin.de/2525/},
     year = {2014}
    }
  • Alexandra Zerck, “Optimal precursor ion selection for LC-MS/MS based proteomics”, 2014-02-13.
    cite this publication
    @phdthesis{fu_mi_publications2527,
     abstract = {Shotgun proteomics with Liquid Chromatography (LC) coupled to Tandem Mass Spectrometry
      (MS/MS) is a key technology for protein identification and quantitation. Protein identification is
      done indirectly: detected peptide signals are fragmented byMS/MS and their sequence is
      reconstructed. Afterwards, the identified peptides are used to infer the proteins present in a
      sample. The problem of choosing the peptide signals that shall be identified with MS/MS is called
      precursor ion selection. Most workflows use data- dependent acquisition for precursor ion
      selection despite known drawbacks like data redundancy, limited reproducibility or a bias towards
      high-abundance proteins. In this thesis, we formulate optimization problems for different aspects
      of precursor ion selection to overcome these weaknesses. In the first part of this work we develop
      inclusion lists aiming at optimal precursor ion selection given different input information. We
      trace precursor ion selection back to known combinatorial problems and develop linear program (LP)
      formulations. The first method creates an inclusion list given a set of detected features in an
      LC-MS map. We show that this setting is an instance of the Knapsack Problem. The corresponding LP
      can be solved efficiently and yields inclusion lists that schedule more precursors than standard
      methods when the number of precursors per fraction is limited. Furthermore, we develop a method
      for inclusion list creation based on a list of proteins of interest. We employ retention time and
      detectability prediction to infer LC-MS features. Based on peptide detectability, we introduce
      protein detectabilities that reflect the likelihood of detecting and identifying a protein. By
      maximizing the sum of protein detectabilities we create an inclusion list of limited size that
      covers a maximum number of proteins. In the second part of the thesis, we focus on iterative
      precursor ion selection (IPS) with LC-MALDI MS/MS. Here, after a fixed number of acquired MS/MS
      spectra their identification results are evaluated and are used for the next round of precursor
      ion selection. We develop a heuristic which creates a ranked precursor list. The second method,
      IPS LP, is a combination of the two inclusion list scenarios presented in the first part.
      Additionally, a protein-based exclusion is part of the objective function. For evaluation, we
      compared both IPS methods to a static inclusion list (SPS) created before the beginning of MS/MS
      acquisition. We simulated precursor ion selection on three data sets of different complexity and
      show that IPS LP can identify the same number of proteins with fewer selected precursors. This
      improvement is especially pronounced for low abundance proteins. Additionally, we show that IPS LP
      decreases the bias to high abundance proteins. All presented algorithms were implemented in
      OpenMS, a software library for mass spectrometry. Finally, we present an online tool for IPS that
      has direct access to the instrument and controls the measurement.},
     author = {Alexandra Zerck},
     month = {February},
     school = {Freie Universit{\"a}t Berlin},
     title = {Optimal precursor ion selection for LC-MS/MS based proteomics},
     url = {http://publications.imp.fu-berlin.de/2527/},
     year = {2014}
    }
  • Chris Bauer, “Exploiting Proteomics Data”, 2014-02-20.
    cite this publication
    @phdthesis{fu_mi_publications2537,
     abstract = {Proteomics plays a central role in understanding complex disease mechanisms, especially
      since it is well known that the effectors of biological functions are mostly proteins. Beside
      classical gel-based techniques especially Mass Spectrometry (MS) has emerged as the standard
      technique for proteomics experiments. MS-based proteomics has evolved into several different and
      partly complementary technologies. In this thesis we have analyzed data generated by the three
      complementary technologies: Matrix-Assisted Laser Desorption/Ionization (MALDI), Isobaric Tags for
      Relative and Absolute Quantitation (iTRAQ) and 2D Difference Gel Electrophoresis (DIGE). The three
      technologies are applied to an obesity-induced mouse model in order to gain relevant knowledge on
      biological processes involved in diabetes. The primary goal of this thesis is to develop and
      implement specifically tailored data analysis methods for each technology with the aim to improve
      quality and reliability of the results compared to standard evaluation workflows. The developed
      methods benefit from the fact that in proteomics a single protein is typically represented by
      several peptides showing more or less similar measurements. Combining this similarity information
      and advanced statistical testing, we are able to identify sets of potential biomarkers that may
      play an important role in diabetes disease mechanisms. The identified biomarkers are very well
      suited for building a classification engine to predict disease relations. However, peptides
      derived from the same protein may also show contradictory quantitations (e.g. a protein is
      two-fold up regulated and two- fold down regulated at the same time). This could be due to
      technical artifacts or biological properties (e.g. protein isoforms). We try to resolve these
      contradictions with PPINGUIN, a workflow developed for the reliable quantitation of iTRAQ
      experiments. Application of the developed methods leads to improved results compared to standard
      data evaluation methods. The three technologies have a complementary character and therefore a
      direct comparison is difficult and shows only a small overlap. But a comparison based on the more
      abstract level of biochemical pathways shows a surprisingly good agreement of the results. In
      order to better understand the complex processes involved in diabetes a major challenge remains in
      integrating the results with other ?omics? technologies.},
     author = {Chris Bauer},
     month = {February},
     school = {Freie Universit{\"a}t Berlin},
     title = {Exploiting Proteomics Data},
     url = {http://publications.imp.fu-berlin.de/2537/},
     year = {2014}
    }

2013

  • E. Siragusa, D. Weese, K. Reinert, “Fast and accurate read mapping with approximate seeds and multiple backtracking”, vol. 41, iss. 7, 2013-01-28.
    cite this publication
    @article{fu_mi_publications1161,
     abstract = {We present Masai, a read mapper representing the state-of-the-art in terms of speed and
      accuracy. Our tool is an order of magnitude faster than RazerS 3 and mrFAST, 2?4 times faster and
      more accurate than Bowtie 2 and BWA. The novelties of our read mapper are filtration with
      approximate seeds and a method for multiple backtracking. Approximate seeds, compared with exact
      seeds, increase filtration specificity while preserving sensitivity. Multiple backtracking
      amortizes the cost of searching a large set of seeds by taking advantage of the repetitiveness of
      next-generation sequencing data. Combined together, these two methods significantly speed up
      approximate search on genomic data sets. Masai is implemented in C++ using the SeqAn library. The
      source code is distributed under the BSD license and binaries for Linux, Mac OS X and Windows can
      be freely downloaded from http://www.seqan.de/projects/masai.},
     author = {E. Siragusa and D. Weese and K. Reinert},
     journal = {Oxford Journals},
     month = {January},
     number = {7},
     pages = {e78},
     publisher = {Oxford University Press},
     title = {Fast and accurate read mapping with approximate seeds and multiple backtracking},
     url = {http://publications.imp.fu-berlin.de/1161/},
     volume = {41},
     year = {2013}
    }
  • E. Siragusa, D. Weese, K. Reinert, “Scalable string similarity search/join with approximate seeds and multiple backtracking”, 2013.
    cite this publication
    @inproceedings{fu_mi_publications1225,
     abstract = {We present in this paper scalable algorithms for optimal string similarity search and
      join. Our methods are variations of those applied in Masai [15], our recently published tool for
      mapping high-throughput DNA sequencing data with unpreceded speed and accuracy. The key features
      of our approach are filtration with approximate seeds and methods for multiple backtracking.
      Approximate seeds, compared to exact seeds, increase filtration specificity while preserving
      sensitivity. Multiple backtracking amortizes the cost of searching a large set of seeds. Combined
      together, these two methods significantly speed up string similarity search and join operations.
      Our tool is implemented in C++ and OpenMP using the SeqAn library. The source code is distributed
      under the BSD license and can be freely downloaded from http://www.seqan.de/projects/edbt2013.},
     address = {New York, NY, USA},
     author = {E. Siragusa and D. Weese and K. Reinert},
     booktitle = {Proceedings of the Joint EDBT/ICDT 2013 Workshops},
     keywords = {approximate seeds, backtracking, banded Myers bit-vector, banded dynamic programming,
      filtration, radix tree, suffix tree},
     pages = {370--374},
     publisher = {ACM},
     series = {EDBT '13},
     title = {Scalable string similarity search/join with approximate seeds and multiple backtracking},
     url = {http://publications.imp.fu-berlin.de/1225/},
     year = {2013}
    }
  • D. Weese, “Indices and Applications in High-Throughput Sequencing”, p. 196, 2013-06-05.
    cite this publication
    @phdthesis{fu_mi_publications1288,
     abstract = {Recent advances in sequencing technology allow to produce billions of base pairs per
      day in the form of reads of length 100 bp an longer and current developments promise the personal
      \$1,000 genome in a couple of years. The analysis of these unprecedented amounts of data demands
      for efficient data structures and algorithms. One such data structures is the substring index,
      that represents all substrings or substrings up to a certain length contained in a given text. In
      this thesis we propose 3 substring indices, which we extend to be applicable to millions of
      sequences. We devise internal and external memory construction algorithms and a uniform framework
      for accessing the generalized suffix tree. Additionally we propose different index-based
      applications, e.g. exact and approximate pattern matching and different repeat search algorithms.
      Second, we present the read mapping tool RazerS, which aligns millions of single or paired-end
      reads of arbitrary lengths to their potential genomic origin using either Hamming or edit
      distance. Our tool can work either lossless or with a user-defined loss rate at higher speeds.
      Given the loss rate, we present a novel approach that guarantees not to lose more reads than
      specified. This enables the user to adapt to the problem at hand and provides a seamless tradeoff
      between sensitivity and running time. We compare RazerS with other state-of-the-art read mappers
      and show that it has the highest sensitivity and a comparable performance on various real-world
      datasets. At last, we propose a general approach for frequency based string mining, which has many
      applications, e.g. in contrast data mining. Our contribution is a novel and lightweight algorithm
      that is faster and uses less memory than the best available algorithms. We show its applicability
      for mining multiple databases with a variety of frequency constraints. As such, we use the notion
      of entropy from information theory to generalize the emerging substring mining problem to multiple
      databases. To demonstrate the improvement of our algorithm we compared to recent approaches on
      real-world experiments of various string domains, e.g. natural language, DNA, or protein
      sequences.},
     author = {D. Weese},
     keywords = {HTS; full-text index; frequency string mining; read mapping; SeqAn},
     month = {June},
     school = {Freie Universit{\"a}t Berlin},
     title = {Indices and Applications in High-Throughput Sequencing},
     url = {http://publications.imp.fu-berlin.de/1288/},
     year = {2013}
    }
  • T. Steijger, J. F. Abril, P. G. Engström, F. Kokocinski, The RGASP Consortium, H. Richard, M. H. Schulz, D. Weese, T. Hubbard, R. GuigĂł, J. Harrow, P. Bertone, “Assessment of transcript reconstruction methods for RNA-seq”, vol. 10, iss. 12, 2013-11-03.
    cite this publication
    @article{fu_mi_publications1380,
     abstract = {We evaluated 25 protocol variants of 14 independent computational methods for exon
      identification, transcript reconstruction and expression-level quantification from RNA-seq data.
      Our results show that most algorithms are able to identify discrete transcript components with
      high success rates but that assembly of complete isoform structures poses a major challenge even
      when all constituent elements are identified. Expression-level estimates also varied widely across
      methods, even when based on similar transcript models. Consequently, the complexity of higher
      eukaryotic genomes imposes severe limitations on transcript recall and splice product
      discrimination that are likely to remain limiting factors for the analysis of current-generation
      RNA-seq data.},
     author = {T. Steijger and J. F. Abril and P. G. Engstr{\"o}m and F. Kokocinski and The RGASP
      Consortium and H. Richard and M. H. Schulz and D. Weese and T. Hubbard and R. Guig{\'o} and J.
      Harrow and P. Bertone},
     journal = {Nature Methods},
     month = {November},
     number = {12},
     pages = {1177--1184},
     publisher = {Nature Publishing Group},
     title = {Assessment of transcript reconstruction methods for RNA-seq},
     url = {http://publications.imp.fu-berlin.de/1380/},
     volume = {10},
     year = {2013}
    }
  • V. Neu, C. Bielow, I. Gostomski, R. Wintringer, R. Braun, K. Reinert, P. Schneider, H. Stuppner, C. Huber, “Rapid and Comprehensive Impurity Profiling of Synthetic Thyroxine by Ultrahigh-Performance Liquid Chromatography–High-Resolution Mass Spectrometry”, vol. 85, iss. 6, 2013-02-08.
    cite this publication
    @article{fu_mi_publications1397,
     abstract = {Rapid and efficient quality control according to the public authority regulations is
      mandatory to guarantee safety of the pharmaceuticals and to save resources in the pharmaceutical
      industry. In the case of so-called "grandfather products" like the synthetic thyroid hormone
      thyroxine, strict regulations enforce a detailed chemical analysis in order to characterize
      potentially toxic or pharmacologically relevant impurities. We report a straightforward workflow
      for the comprehensive impurity profiling of synthetic thyroid hormones and impurities employing
      ultrahigh-performance liquid chromatography (UHPLC) hyphenated to high-resolution mass
      spectrometry (HRMS). Five different batches of synthetic thyroxin were analyzed resulting in the
      detection of 71 impurities within 3 min total analysis time. Structural elucidation of the
      compounds was accomplished via a combination of accurate mass measurements, computer based
      calculations of molecular formulas, multistage high-resolution mass spectrometry (HRMS(n)), and
      nuclear magnetic resonance spectroscopy, which enabled the identification of 71 impurities, of
      which 47 have been unknown so far. Thirty of the latter were structurally elucidated, including
      products of deiodination, aliphatic chain oxidation, as well as dimeric compounds as new class of
      thyroid hormone derivatives. Limits of detection for the thyroid compounds were in the 6 ng/mL
      range for negative electrospray ionization mass spectrometric detection in full scan mode. Within
      day and day-to-day repeatabilities of retention times and peak areas were below 0.5\% and 3.5\%
      R.SD. The performance characteristics of the method in terms of robustness and information content
      clearly show that UHPLC-HRMS is adequate for the rapid and reliable detection, identification, and
      semiquantitative determination of trace levels of impurities in synthetic pharmaceuticals.},
     author = {V. Neu and C. Bielow and I. Gostomski and R. Wintringer and R. Braun and K. Reinert and
      P. Schneider and H. Stuppner and C. Huber},
     journal = {Analytical Chemistry},
     month = {February},
     number = {6},
     pages = {3309--3317},
     publisher = {American Chemical Society},
     title = {Rapid and Comprehensive Impurity Profiling of Synthetic Thyroxine by Ultrahigh-Performance
      Liquid Chromatography?High-Resolution Mass Spectrometry},
     url = {http://publications.imp.fu-berlin.de/1397/},
     volume = {85},
     year = {2013}
    }
  • V. Neu, C. Bielow, P. Schneider, K. Reinert, H. Stuppner, C. Huber, “Investigation of Reaction Mechanisms of Drug Degradation in the Solid State: A Kinetic Study Implementing Ultrahigh-Performance Liquid Chromatography and High-Resolution Mass Spectrometry for Thermally Stressed Thyroxine”, vol. 85, iss. 4, 2013-01-12.
    cite this publication
    @article{fu_mi_publications1398,
     abstract = {A reaction scheme was derived for the thermal degradation of thyroxine in the solid
      state, using data obtained from ultrahigh-performance liquid chromatography and high-resolution
      mass spectrometry (UHPLC-HRMS). To study the reaction mechanism and kinetics of the thermal
      degradation of the pharmaceutical in the solid state, a workflow was developed by generating
      compound-specific, time-dependent degradation or formation curves of at least 13 different
      degradation products. Such curves allowed one to distinguish between first- and second-generation
      degradation products, as well as impurities resulting from chemical synthesis. The structures of
      the degradation products were derived from accurate molecular masses and multistage mass
      spectrometry. Deiodination and oxidative side chain degradation were found to be the major
      degradation reactions, resulting in the formation of deiodinated thyroxines, as well as acetic
      acid, benzoic acid, formaldehyde, acetamide, hydroxyacetic acid, oxoacetic acid, hydroxyacetamide,
      or oxoacetamide derivatives of thyroxine or deiodinated thyroxine. Upon additional structural
      verification of mass spectrometric data using nuclear magnetic resonance spectroscopy, this
      comprehensive body of data sheds light on an elaborate, radical-driven reaction scheme, explaining
      the presence or formation of impurities in thermally stressed thyroxine.},
     author = {V. Neu and C. Bielow and P. Schneider and K. Reinert and H. Stuppner and C. Huber},
     journal = {Analytical Chemistry},
     month = {January},
     number = {4},
     pages = {2385--2390},
     publisher = {American Chemical Society},
     title = {Investigation of Reaction Mechanisms of Drug Degradation in the Solid State: A Kinetic
      Study Implementing Ultrahigh-Performance Liquid Chromatography and High-Resolution Mass
      Spectrometry for Thermally Stressed Thyroxine},
     url = {http://publications.imp.fu-berlin.de/1398/},
     volume = {85},
     year = {2013}
    }
  • A. Zerck, E. Nordhoff, H. Lehrach, K. Reinert, “Optimal precursor ion selection for LC-MALDI MS/MS”, vol. 14, iss. 1, 2013-02-18.
    cite this publication
    @article{fu_mi_publications1400,
     abstract = {Background Liquid chromatography mass spectrometry (LC-MS) maps in shotgun proteomics
      are often too complex to select every detected peptide signal for fragmentation by tandem mass
      spectrometry (MS/MS). Standard methods for precursor ion selection, commonly based on data
      dependent acquisition, select highly abundant peptide signals in each spectrum. However, these
      approaches produce redundant information and are biased towards high-abundance proteins. Results
      We present two algorithms for inclusion list creation that formulate precursor ion selection as an
      optimization problem. Given an LC-MS map, the first approach maximizes the number of selected
      precursors given constraints such as a limited number of acquisitions per RT fraction. Second, we
      introduce a protein sequence-based inclusion list that can be used to monitor proteins of
      interest. Given only the protein sequences, we create an inclusion list that optimally covers the
      whole protein set. Additionally, we propose an iterative precursor ion selection that aims at
      reducing the redundancy obtained with data dependent LC-MS/MS. We overcome the risk of erroneous
      assignments by including methods for retention time and proteotypicity predictions. We show that
      our method identifies a set of proteins requiring fewer precursors than standard approaches. Thus,
      it is well suited for precursor ion selection in experiments with limited sample amount or
      analysis time. Conclusions We present three approaches to precursor ion selection with LC-MALDI
      MS/MS. Using a well-defined protein standard and a complex human cell lysate, we demonstrate that
      our methods outperform standard approaches. Our algorithms are implemented as part of OpenMS and
      are available under http://www.openms.de.},
     author = {A. Zerck and E. Nordhoff and H. Lehrach and K. Reinert},
     journal = {BMC Bioinformatics},
     month = {February},
     number = {1},
     pages = {56},
     publisher = {BioMed Central},
     title = {Optimal precursor ion selection for LC-MALDI MS/MS},
     url = {http://publications.imp.fu-berlin.de/1400/},
     volume = {14},
     year = {2013}
    }
  • L. de la Garza, J. KrĂŒger, Ch. SchĂ€rfe, M. Röttig, S. Aiche, K. Reinert, O. Kohlbacher, “From the Desktop to the Grid: conversion of KNIME Workflows to gUSE”, 2013.
    cite this publication
    @inproceedings{fu_mi_publications1441,
     abstract = {The Konstanz Information Miner is a user-friendly graphical workflow designer with a
      broad user base in industry and academia. Its broad range of embedded tools and its powerful data
      mining and visualization tools render it ideal for scientific workflows. It is thus used more and
      more in a broad range of applications. However, the free version typically runs on a desktop
      computer, restricting users if they want to tap into computing power. The grid and cloud User
      Support Environment is a free and open source project created for parallelized and distributed
      systems, but the creation of workflows with the included components has a steeper learning curve.
      In this work we suggest an easy to implement solution combining the ease-of-use of the Konstanz
      Information Miner with the computational power of distributed computing infrastructures. We
      present a solution permitting the conversion of workflows between the two platforms. This enables
      a convenient development, debugging, and maintenance of scientific workflows on the desktop. These
      workflows can then be deployed on a cloud or grid, thus permitting large-scale computation. To
      achieve our goals, we relied on a Common Tool Description XML file format which describes the
      execution of arbitrary programs in a structured and easily readable and parseable way. In order to
      integrate external programs into we employed the Generic KNIME Nodes extension.},
     author = {L. de la Garza and J. Kr{\"u}ger and Ch. Sch{\"a}rfe and M. R{\"o}ttig and S. Aiche and
      K. Reinert and O. Kohlbacher},
     booktitle = {IWSG (International Workshop on Science Gateways)},
     title = {From the Desktop to the Grid: conversion of KNIME Workflows to gUSE},
     url = {http://publications.imp.fu-berlin.de/1441/},
     year = {2013}
    }
  • S. Aiche, “Inferring Proteolytic Processes from Mass Spectrometry Time Series Data”, 2013-09-30.
    cite this publication
    @phdthesis{fu_mi_publications1445,
     address = {Berlin, Germany},
     author = {S. Aiche},
     month = {September},
     school = {Freie Universit{\"a}t Berlin},
     title = {Inferring Proteolytic Processes from Mass Spectrometry Time Series Data},
     url = {http://publications.imp.fu-berlin.de/1445/},
     year = {2013}
    }
  • S. Andreotti, K. Reinert, S. Canzar, “The duplication-loss small phylogeny problem: from cherries to trees.”, vol. 20, iss. 9, 2013-09.
    cite this publication
    @article{fu_mi_publications1454,
     abstract = {Abstract The reconstruction of the history of evolutionary genome-wide events among a
      set of related organisms is of great biological interest since it can help to reveal the genomic
      basis of phenotypes. The sequencing of whole genomes faciliates the study of gene families that
      vary in size through duplication and loss events, like transfer RNA. However, a high sequence
      similarity often does not allow one to distinguish between orthologs and paralogs. Previous
      methods have addressed this difficulty by taking into account flanking regions of members of a
      family independently. We go one step further by inferring the order of genes of (a set of)
      families for ancestral genomes by considering the order of these genes on sequenced genomes. We
      present a novel branch-and-cut algorithm to solve the two species small phylogeny problem in the
      evolutionary model of duplications and losses. On average, our implementation, DupLoCut, improves
      the running time of a recently proposed method in the experiments on six Vibrionaceae lineages by
      a factor of {\~A}?\&lt;88\&gt;{\^A}?200. Besides the mere improvement in running time, the
      efficiency of our approach allows us to extend our model from cherries of a species tree, that is,
      subtrees with two leaves, to the median of three species setting. Being able to determine the
      median of three species is of key importance to one of the most common approaches to ancestral
      reconstruction, and our experiments show that its repeated computation considerably reduces the
      number of duplications and losses along the tree both on simulated instances comprising 128 leaves
      and a set of Bacillus genomes. Furthermore, in our simulations we show that a reduction in cost
      goes hand in hand with an improvement of the predicted ancestral genomes. Finally, we prove that
      the small phylogeny problem in the duplication-loss model is NP-complete already for two
      species.},
     author = {S. Andreotti and K. Reinert and S. Canzar},
     journal = {Journal of Computational Biology},
     month = {September},
     number = {9},
     pages = {643--59},
     title = {The duplication-loss small phylogeny problem: from cherries to trees.},
     url = {http://publications.imp.fu-berlin.de/1454/},
     volume = {20},
     year = {2013}
    }
  • S. Nahnsen, C. Bielow, K. Reinert, O. Kohlbacher, “Tools for Label-free Peptide Quantification”, vol. 12, iss. 3, 2013-03-01.
    cite this publication
    @article{fu_mi_publications1473,
     abstract = {The increasing scale and complexity of quantitative proteomics studies complicate
      subsequent analysis of the acquired data. Untargeted label-free quantification, based either on
      feature intensities or on spectral counting, is a method that scales particularly well with
      respect to the number of samples. It is thus an excellent alternative to labeling techniques. In
      order to profit from this scalability, however, data analysis has to cope with large amounts of
      data, process them automatically, and do a thorough statistical analysis in order to achieve
      reliable results. We review the state of the art with respect to computational tools for
      label-free quantification in untargeted proteomics. The two fundamental approaches are
      feature-based quantification, relying on the summed-up mass spectrometric intensity of peptides,
      and spectral counting, which relies on the number of MS/MS spectra acquired for a certain protein.
      We review the current algorithmic approaches underlying some widely used software packages and
      briefly discuss the statistical strategies for analyzing the data.},
     author = {S. Nahnsen and C. Bielow and K. Reinert and O. Kohlbacher},
     journal = {Molecular \& Cellular Proteomics},
     month = {March},
     number = {3},
     pages = {549--556},
     title = {Tools for Label-free Peptide Quantification},
     url = {http://publications.imp.fu-berlin.de/1473/},
     volume = {12},
     year = {2013}
    }
  • Anne-Katrin Emde, “Next-generation sequencing algorithms - from read mapping to variant detection”, 2013-12-03.
    cite this publication
    @phdthesis{fu_mi_publications2526,
     abstract = {Next-Generation-Sequencing (NGS) has brought on a revolution in sequence analysis with
      its broad spectrum of applications ranging from genome resequencing to transcriptomics or
      metagenomics, and from fundamental research to diagnostics. The tremendous amounts of data
      necessitate highly efficient computational analysis tools for the wide variety of NGS
      applications. This thesis addresses a broad range of key computational aspects of resequencing
      applications, where a reference genome sequence is known and heavily used for interpretation of
      the newly sequenced sample. It presents tools for read mapping and benchmarking, for partial read
      mapping of small RNA reads and for structural variant/indel detection, and finally tools for
      detecting and genotyping SNVs and short indels. Our tools efficiently scale to large NGS data sets
      and are well-suited for advances in sequencing technology, since their generic algorithm design
      allows handling of arbitrary read lengths and variable error rates. Furthermore, they are
      implemented within the robust C++ library SeqAn, making them open-source, easily available, and
      potentially adaptable for the bioinformatics community. Among other applications, our tools have
      been integrated into a large-scale analysis pipeline and have been applied to large datasets,
      leading to interesting discoveries of human retrocopy variants and insights into the genetic
      causes of X-linked intellectual disabilities.},
     author = {Anne-Katrin Emde},
     month = {December},
     school = {Freie Universit{\"a}t Berlin},
     title = {Next-generation sequencing algorithms - from read mapping to variant detection},
     url = {http://publications.imp.fu-berlin.de/2526/},
     year = {2013}
    }

2012

  • S. Andreotti, G. W. Klau, K. Reinert, “Antilope - A Lagrangian Relaxation Approach to the de novo Peptide Sequencing Problem”, vol. 9, iss. 2, 2012-03.
    cite this publication
    @article{fu_mi_publications1047,
     abstract = {Peptide sequencing from mass spectrometry data is a key step in proteome research.
      Especially de novo sequencing, the identification of a peptide from its spectrum alone, is still a
      challenge even for state-of-the-art algorithmic approaches. In this paper we present ANTILOPE, a
      new fast and flexible approach based on mathematical programming. It builds on the spectrum graph
      model and works with a variety of scoring schemes. ANTILOPE combines Lagrangian relaxation for
      solving an integer linear programming formulation with an adaptation of Yen?s k shortest paths
      algorithm. It shows a significant improvement in running time compared to mixed integer
      optimization and performs at the same speed like other state-of-the-art tools. We also implemented
      a generic probabilistic scoring scheme that can be trained automatically for a dataset of
      annotated spectra and is independent of the mass spectrometer type. Evaluations on benchmark data
      show that ANTILOPE is competitive to the popular state-of-the-art programs PepNovo and NovoHMM
      both in terms of run time and accuracy. Furthermore, it offers increased flexibility in the number
      of considered ion types. ANTILOPE will be freely available as part of the open source proteomics
      library OpenMS.},
     address = {Los Alamitos, CA, USA},
     author = {S. Andreotti and G. W. Klau and K. Reinert},
     journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)},
     month = {March},
     note = {doi: 10.1109/TCBB.2011.59},
     number = {2},
     pages = {385--394},
     publisher = {IEEE Computer Society Press},
     title = {Antilope - A Lagrangian Relaxation Approach to the de novo Peptide Sequencing Problem},
     url = {http://publications.imp.fu-berlin.de/1047/},
     volume = {9},
     year = {2012}
    }
  • S. Aiche, K. Reinert, Ch. SchĂŒtte, D. Hildebrand, H. SchlĂŒter, T. O. F. Conrad, “Inferring Proteolytic Processes from Mass Spectrometry Time Series Data Using Degradation Graphs”, vol. 7, iss. 7, 2012-07-17.
    cite this publication
    @article{fu_mi_publications1143,
     abstract = {Background: Proteases play an essential part in a variety of biological processes.
      Beside their importance under healthy conditions they are also known to have a crucial role in
      complex diseases like cancer. It was shown in the last years that not only the fragments produced
      by proteases but also their dynamics, especially ex vivo, can serve as biomarkers. But so far,
      only a few approaches were taken to explicitly model the dynamics of proteolysis in the context of
      mass spectrometry. Results: We introduce a new concept model proteolytic processes, the
      degradation graph. The degra- dation graph is an extension of the cleavage graph, a data structure
      to reconstruct and visualize the proteolytic process. In contrast to previous approaches we
      extended the model to incorporate endoproteolytic processes and present a method to construct a
      degradation graph from mass spectrometry time-series data. Based on a degradation graph and the
      intensities extracted from the mass spectra it is possible to estimate reaction rates of the
      underlying processes. We further suggest a score to rate different degradation graphs in their
      ability to explain the observed data. This score is used in an iterative heuristic to improve the
      structure of the initially constructed degradation graph. Conclusion: We show that the proposed
      method is able to recover all degraded and generated peptides, the underlying reactions, and the
      reaction rates of proteolytic processes based on mass spectrometry time-series data. We use
      simulated and real data to demonstrate that a given process can be reconstructed even in the
      presence of extensive noise, isobaric signals and false identications. While the model is
      currently only validated on peptide data it is also applicable to proteins, as long as the
      necessary time series data can be produced.},
     author = {S. Aiche and K. Reinert and Ch. Sch{\"u}tte and D. Hildebrand and H. Schl{\"u}ter and T.
      O. F. Conrad},
     journal = {PLoS ONE},
     month = {July},
     number = {7},
     pages = {e40656},
     publisher = {Public Library of Science},
     title = {Inferring Proteolytic Processes from Mass Spectrometry Time Series Data Using Degradation
      Graphs},
     url = {http://publications.imp.fu-berlin.de/1143/},
     volume = {7},
     year = {2012}
    }
  • D. Weese, M. Holtgrewe, K. Reinert, “RazerS 3: Faster, fully sensitive read mapping”, vol. 28, iss. 20, 2012-08-24.
    cite this publication
    @article{fu_mi_publications1159,
     abstract = {Motivation: During the last years NGS sequencing has become a key technology for many
      applications in the biomedical sciences. Throughput continues to increase and new protocols
      provide longer reads than currently available. In almost all applications, read mapping is a first
      step. Hence, it is crucial to have algorithms and implementations that perform fast, with high
      sensitivity, and are able to deal with long reads and a large absolute number of indels. Results:
      RazerS is a read mapping program with adjustable sensitivity based on counting q-grams. In this
      work we propose the successor RazerS 3 which now supports shared-memory parallelism, an additional
      seed-based filter with adjustable sensitivity, a much faster, banded version of the Myers?
      bit-vector algorithm for verification, memory saving measures and support for the SAM output
      format. This leads to a much improved performance for mapping reads, in particular long reads with
      many errors. We extensively compare RazerS 3 with other popular read mappers and show that its
      results are often superior to them in terms of sensitivity while exhibiting practical and often
      competetive run times. In addition, RazerS 3 works without a precomputed index. Availability and
      Implementation: Source code and binaries are freely available for download at
      http://www.seqan.de/projects/razers. RazerS 3 is implemented in C++ and OpenMP under a GPL license
      using the SeqAn library and supports Linux, Mac OS X, and Windows.},
     author = {D. Weese and M. Holtgrewe and K. Reinert},
     journal = {Bioinformatics},
     month = {August},
     number = {20},
     pages = {2592--2599},
     publisher = {Oxford University Press},
     title = {RazerS 3: Faster, fully sensitive read mapping},
     url = {http://publications.imp.fu-berlin.de/1159/},
     volume = {28},
     year = {2012}
    }
  • A.-K. Emde, M. H. Schulz, D. Weese, R. Sun, M. Vingron, V. M. Kalscheuer, S. A. Haas, K. Reinert, “Detecting genomic indel variants with exact breakpoints in single- and paired-end sequencing data using SplazerS”, vol. 28, iss. 5, 2012-01-11.
    cite this publication
    @article{fu_mi_publications1160,
     abstract = {Motivation: The reliable detection of genomic variation in resequencing data is still a
      major challenge, especially for variants larger than a few base pairs. Sequencing reads crossing
      boundaries of structural variation carry the potential for their identification, but are difficult
      to map. Results: Here we present a method for ?split? read mapping, where prefix and suffix match
      of a read may be interrupted by a longer gap in the read-to-reference alignment. We use this
      method to accurately detect medium-sized insertions and long deletions with precise breakpoints in
      genomic resequencing data. Compared with alternative split mapping methods, SplazerS significantly
      improves sensitivity for detecting large indel events, especially in variant-rich regions. Our
      method is robust in the presence of sequencing errors as well as alignment errors due to genomic
      mutations/divergence, and can be used on reads of variable lengths. Our analysis shows that
      SplazerS is a versatile tool applicable to unanchored or single-end as well as anchored paired-end
      reads. In addition, application of SplazerS to targeted resequencing data led to the interesting
      discovery of a complete, possibly functional gene retrocopy variant. Availability: SplazerS is
      available from http://www.seqan.de/projects/ splazers.},
     author = {A.-K. Emde and M. H. Schulz and D. Weese and R. Sun and M. Vingron and V. M. Kalscheuer
      and S. A. Haas and K. Reinert},
     journal = {Bioinformatics},
     month = {January},
     number = {5},
     pages = {619--627},
     publisher = {Oxford University Press},
     title = {Detecting genomic indel variants with exact breakpoints in single- and paired-end
      sequencing data using SplazerS},
     url = {http://publications.imp.fu-berlin.de/1160/},
     volume = {28},
     year = {2012}
    }
  • B. Kehr, K. Reinert, A. E. Darling, B. Raphael, J. Tang, “Hidden Breakpoints in Genome Alignments ”, vol. 7534, 2012.
    cite this publication
    @incollection{fu_mi_publications1168,
     abstract = {During the course of evolution, an organism?s genome can undergo changes that affect
      the large-scale structure of the genome. These changes include gene gain, loss, duplication,
      chromosome fusion, fission, and rearrangement. When gene gain and loss occurs in addition to other
      types of rearrangement, breakpoints of rearrangement can exist that are only detectable by
      comparison of three or more genomes. An arbitrarily large number of these ?hidden? breakpoints can
      exist among genomes that exhibit no rearrangements in pairwise comparisons. We present an
      extension of the multichromosomal breakpoint median problem to genomes that have undergone gene
      gain and loss. We then demonstrate that the median distance among three genomes can be used to
      calculate a lower bound on the number of hidden breakpoints present. We provide an implementation
      of this calculation including the median distance, along with some practical improvements on the
      time complexity of the underlying algorithm. We apply our approach to measure the abundance of
      hidden breakpoints in simulated data sets under a wide range of evolutionary scenarios. We
      demonstrate that in simulations the hidden breakpoint counts depend strongly on relative rates of
      inversion and gene gain/loss. Finally we apply current multiple genome aligners to the simulated
      genomes, and show that all aligners introduce a high degree of error in hidden breakpoint counts,
      and that this error grows with evolutionary distance in the simulation. Our results suggest that
      hidden breakpoint error may be pervasive in genome alignments.},
     address = {Berlin},
     author = {B. Kehr and K. Reinert and A. E. Darling},
     booktitle = {Lecture Notes in Computer Science: Algorithms in Bioinformatics},
     editor = {B. Raphael and J. Tang},
     pages = {391--403},
     publisher = {Springer-Verlag},
     title = {Hidden Breakpoints in Genome Alignments},
     url = {http://publications.imp.fu-berlin.de/1168/},
     volume = {7534},
     year = {2012}
    }
  • J. Junker, C. Bielow, A. Bertsch, M. Sturm, K. Reinert, O. Kohlbacher, “TOPPAS: a graphical workflow editor for the analysis of high-throughput proteomics data”, vol. 11, iss. 7, 2012-07-06.
    cite this publication
    @article{fu_mi_publications1396,
     abstract = {Mass spectrometry coupled to high-performance liquid chromatography (HPLC-MS) is
      evolving more quickly than ever. A wide range of different instrument types and experimental
      setups are commonly used. Modern instruments acquire huge amounts of data, thus requiring tools
      for an efficient and automated data analysis. Most existing software for analyzing HPLC-MS data is
      monolithic and tailored toward a specific application. A more flexible alternative consists of
      pipeline-based tool kits allowing the construction of custom analysis workflows from small
      building blocks, e.g., the Trans Proteomics Pipeline (TPP) or The OpenMS Proteomics Pipeline
      (TOPP). One drawback, however, is the hurdle of setting up complex workflows using command line
      tools. We present TOPPAS, The OpenMS Proteomics Pipeline ASsistant, a graphical user interface
      (GUI) for rapid composition of HPLC-MS analysis workflows. Workflow construction reduces to simple
      drag-and-drop of analysis tools and adding connections in between. Integration of external tools
      into these workflows is possible as well. Once workflows have been developed, they can be deployed
      in other workflow management systems or batch processing systems in a fully automated fashion. The
      implementation is portable and has been tested under Windows, Mac OS X, and Linux. TOPPAS is
      open-source software and available free of charge at http://www.OpenMS.de/TOPPAS .},
     author = {J. Junker and C. Bielow and A. Bertsch and M. Sturm and K. Reinert and O. Kohlbacher},
     journal = {J. Proteome Res.},
     month = {July},
     number = {7},
     pages = {3914--3920},
     publisher = {ACS Publications},
     title = {TOPPAS: a graphical workflow editor for the analysis of high-throughput proteomics data},
     url = {http://publications.imp.fu-berlin.de/1396/},
     volume = {11},
     year = {2012}
    }
  • C. Bielow, “Quantification and Simulation of Liquid Chromatography-Mass Spectrometry Data”, 2012-10-29.
    cite this publication
    @phdthesis{fu_mi_publications1444,
     abstract = {Computational mass spectrometry is a fast evolving field that has attracted increased
      attention over the last couple of years. The performance of software solutions determines the
      success of analysis to a great extent. New algorithms are required to reflect new experimental
      procedures and deal with new instrument generations. One essential component of algorithm
      development is the validation (as well as comparison) of software on a broad range of data sets.
      This requires a gold standard (or so-called ground truth), which is usually obtained by manual
      annotation of a real data set. Comprehensive manually annotated public data sets for mass
      spectrometry data are labor-intensive to produce and their quality strongly depends on the skill
      of the human expert. Some parts of the data may even be impossible to annotate due to high levels
      of noise or other ambiguities. Furthermore, manually annotated data is usually not available for
      all steps in a typical computational analysis pipeline. We thus developed the most comprehensive
      simulation software to date, which allows to generate multiple levels of ground truth and features
      a plethora of settings to reflect experimental conditions and instrument settings. The simulator
      is used to generate several distinct types of data. The data are subsequently employed to evaluate
      existing algorithms. Additionally, we employ simulation to determine the influence of instrument
      attributes and sample complexity on the ability of algorithms to recover information. The results
      give valuable hints on how to optimize experimental setups. Furthermore, this thesis introduces
      two quantitative approaches, namely a decharging algorithm based on integer linear programming and
      a new workflow for identification of differentially expressed proteins for a large in vitro study
      on toxic compounds. Decharging infers the uncharged mass of a peptide (or protein) by clustering
      all its charge variants. The latter occur frequently under certain experimental conditions. We
      employ simulation to show that decharging is robust against missing values even for high
      complexity data and that the algorithm outperforms other solutions in terms of mass accuracy and
      run time on real data. The last part of this thesis deals with a new state-of-the-art workflow for
      protein quantification based on isobaric tags for relative and absolute quantitation (iTRAQ). We
      devise a new approach to isotope correction, propose an experimental design, introduce new metrics
      of iTRAQ data quality, and confirm putative properties of iTRAQ data using a novel approach. All
      tools developed as part of this thesis are implemented in OpenMS, a C++ library for computational
      mass spectrometry.},
     address = {Berlin, Germany},
     author = {C. Bielow},
     month = {October},
     school = {Freie Universit{\"a}t Berlin},
     title = {Quantification and Simulation of Liquid Chromatography-Mass Spectrometry Data},
     url = {http://publications.imp.fu-berlin.de/1444/},
     year = {2012}
    }
  • Chris Bielow, “Quantification and simulation of liquid chromatography-mass spectrometry data”, 2012-11-16.
    cite this publication
    @phdthesis{fu_mi_publications2540,
     abstract = {Computational mass spectrometry is a fast evolving field that has attracted increased
      attention over the last couple of years. The performance of software solutions determines the
      success of analysis to a great extent. New algorithms are required to reflect new experimental
      procedures and deal with new instrument generations. One essential component of algorithm
      development is the validation (as well as comparison) of software on a broad range of data sets.
      This requires a gold standard (or so-called ground truth), which is usually obtained by manual
      annotation of a real data set. Comprehensive manually annotated public data sets for mass
      spectrometry data are labor- intensive to produce and their quality strongly depends on the skill
      of the human expert. Some parts of the data may even be impossible to annotate due to high levels
      of noise or other ambiguities. Furthermore, manually annotated data is usually not available for
      all steps in a typical computational analysis pipeline. We thus developed the most comprehensive
      simulation software to date, which allows to generate multiple levels of ground truth and features
      a plethora of settings to reflect experimental conditions and instrument settings. The simulator
      is used to generate several distinct types of data. The data are subsequently employed to evaluate
      existing algorithms. Additionally, we employ simulation to determine the influence of instrument
      attributes and sample complexity on the ability of algorithms to recover information. The results
      give valuable hints on how to optimize experimental setups. Furthermore, this thesis introduces
      two quantitative approaches, namely a decharging algorithm based on integer linear programming and
      a new workflow for identification of differentially expressed proteins for a large in vitro study
      on toxic compounds. Decharging infers the uncharged mass of a peptide (or protein) by clustering
      all its charge variants. The latter occur frequently under certain experimental conditions. We
      employ simulation to show that decharging is robust against missing values even for high
      complexity data and that the algorithm outperforms other solutions in terms of mass accuracy and
      run time on real data. The last part of this thesis deals with a new state-of-the-art workflow for
      protein quantification based on isobaric tags for relative and absolute quantitation (iTRAQ). We
      devise a new approach to isotope correction, propose an experimental design, introduce new metrics
      of iTRAQ data quality, and confirm putative properties of iTRAQ data using a novel approach. All
      tools developed as part of this thesis are implemented in OpenMS, a C++ library for computational
      mass spectrometry.},
     author = {Chris Bielow},
     month = {November},
     school = {Freie Universit{\"a}t Berlin},
     title = {Quantification and simulation of liquid chromatography-mass spectrometry data},
     url = {http://publications.imp.fu-berlin.de/2540/},
     year = {2012}
    }

2011

  • C. Bielow, S. Aiche, S. Andreotti, K. Reinert, “MSSimulator: Simulation of Mass Spectrometry Data”, vol. 10, iss. 7, 2011-07.
    cite this publication
    @article{fu_mi_publications1066,
     abstract = {Mass spectrometry coupled to liquid chromatography (LC-MS and LC-MS/MS) is commonly
      used to analyze the protein content of biological samples in large scale studies, enabling
      quantitation and identification of proteins and peptides using a wide range of experimental
      protocols, algorithms, and statistical models to analyze the data. Currently it is difficult to
      compare the plethora of algorithms for these tasks. So far, curated benchmark data exists for
      peptide identification algorithms but data that represents a ground truth for the evaluation of
      LC-MS data is limited. Hence there have been attempts to simulate such data in a controlled
      fashion to evaluate and compare algorithms. We present MSSimulator, a simulation software for
      LC-MS and LC-MS/MS experiments. Starting from a list of proteins from a FASTA file,the simulation
      will perform in-silico digestion, retention time prediction, ionization filtering, and raw signal
      simulation (including MS/MS), while providing many options to change the properties of the
      resultingdata like elution profile shape, resolution and sampling rate. Several protocols for
      SILAC, iTRAQ or MS(E) are available, in addition to the usual label-free approach, making
      MSSimulator the most comprehensive simulator for LC-MS and LC-MS/MS data.},
     author = {C. Bielow and S. Aiche and S. Andreotti and K. Reinert},
     journal = {Journal of Proteome Research},
     month = {July},
     number = {7},
     pages = {2922--2929},
     title = {MSSimulator: Simulation of Mass Spectrometry Data},
     url = {http://publications.imp.fu-berlin.de/1066/},
     volume = {10},
     year = {2011}
    }
  • C. Bielow, C. Gröpl, O. Kohlbacher, K. Reinert, “Bioinformatics for qualitative and quantitative proteomics.”, vol. 719, 2011-01.
    cite this publication
    @incollection{fu_mi_publications1067,
     abstract = {Mass spectrometry is today a key analytical technique to elucidate the amount and
      content of proteins expressed in a certain cellular context. The degree of automation in
      proteomics has yet to reach that of genomic techniques, but even current technologies make a
      manual inspection of the data infeasible. This article addresses the key algorithmic problems
      bioinformaticians face when handling modern proteomic samples and shows common solutions to them.
      We provide examples on how algorithms can be combined to build relatively complex analysis
      pipelines, point out certain pitfalls and aspects worth considering and give a list of current
      state-of-the-art tools.},
     author = {C. Bielow and C. Gr{\"o}pl and O. Kohlbacher and K. Reinert},
     booktitle = {Bioinformatics for Omics Data Methods and Protocols},
     journal = {Methods in molecular biology (Clifton, N.J.)},
     month = {January},
     pages = {331--49},
     publisher = {Humana Press},
     title = {Bioinformatics for qualitative and quantitative proteomics.},
     url = {http://publications.imp.fu-berlin.de/1067/},
     volume = {719},
     year = {2011}
    }
  • M. Holtgrewe, A.-K. Emde, D. Weese, K. Reinert, “A Novel And Well-Defined Benchmarking Method For Second Generation Read Mapping”, vol. 12, iss. 120, 2011-05-26.
    cite this publication
    @article{fu_mi_publications1072,
     abstract = {Background Second generation sequencing technologies yield DNA sequence data at ultra
      high-throughput. Common to most biological applications is a mapping of the reads to an almost
      identical or highly similar reference genome. The assessment of the quality of read mapping
      results is not straightforward and has not been formalized so far. Hence, it has not been easy to
      compare different read mapping approaches in a unified way and to determine which program is the
      best for what task. Results We present a new benchmark method, called Rabema (Read Alignment
      BEnchMArk), for read mappers. It consists of a strict definition of the read mapping problem and
      of tools to evaluate the result of arbitrary read mappers supporting the SAM output format.
      Conclusions We show the usefulness of the benchmark program by performing a comparison of popular
      read mappers. The tools supporting the benchmark are licensed under the GPL and available from
      http://www.seqan.de/projects/rabema.html.},
     author = {M. Holtgrewe and A.-K. Emde and D. Weese and K. Reinert},
     journal = {BMC Bioinformatics},
     month = {May},
     number = {120},
     publisher = {BioMed Central},
     title = {A Novel And Well-Defined Benchmarking Method For Second Generation Read Mapping},
     url = {http://publications.imp.fu-berlin.de/1072/},
     volume = {12},
     year = {2011}
    }
  • B. Kehr, D. Weese, K. Reinert, “STELLAR: fast and exact local alignments”, vol. 12, iss. S9, 2011-10-03.
    cite this publication
    @article{fu_mi_publications1092,
     abstract = {Background Large-scale comparison of genomic sequences requires reliable tools for the
      search of local alignments. Practical local aligners are in general fast, but heuristic, and hence
      sometimes miss significant matches. Results We present here the local pairwise aligner STELLAR
      that has full sensitivity for {\ensuremath{\epsilon}}-alignments, i.e. guarantees to report all
      local alignments of a given minimal length and maximal error rate. The aligner is composed of two
      steps, filtering and verification. We apply the SWIFT algorithm for lossless filtering, and have
      developed a new verification strategy that we prove to be exact. Our results on simulated and real
      genomic data confirm and quantify the conjecture that heuristic tools like BLAST or BLAT miss a
      large percentage of significant local alignments. Conclusions STELLAR is very practical and fast
      on very long sequences which makes it a suitable new tool for finding local alignments between
      genomic sequences under the edit distance model. Binaries are freely available for Linux, Windows,
      and Mac OS X at http://www.seqan.de/projects/stellar. The source code is freely distributed with
      the SeqAn C++ library version 1.3 and later at http://www.seqan.de.},
     author = {B. Kehr and D. Weese and K. Reinert},
     journal = {BMC Bioinformatics},
     month = {October},
     number = {S9},
     pages = {S15},
     publisher = {BioMed Central},
     title = {STELLAR: fast and exact local alignments},
     url = {http://publications.imp.fu-berlin.de/1092/},
     volume = {12},
     year = {2011}
    }
  • S. Böcker, B. Kehr, F. Rasche, “Determination of Glycan Structure from Tandem Mass Spectra”, vol. 8, iss. 4, 2011-07.
    cite this publication
    @article{fu_mi_publications1132,
     abstract = {Glycans are molecules made from simple sugars that form complex tree structures.
      Glycans constitute one of the most important protein modifications and identification of glycans
      remains a pressing problem in biology. Unfortunately, the structure of glycans is hard to predict
      from the genome sequence of an organism. In this paper, we consider the problem of deriving the
      topology of a glycan solely from tandem mass spectrometry (MS) data. We study, how to generate
      glycan tree candidates that sufficiently match the sample mass spectrum, avoiding the
      combinatorial explosion of glycan structures. Unfortunately, the resulting problem is known to be
      computationally hard. We present an efficient exact algorithm for this problem based on
      fixed-parameter algorithmics that can process a spectrum in a matter of seconds. We also report
      some preliminary results of our method on experimental data, combining it with a preliminary
      candidate evaluation scheme. We show that our approach is fast in applications, and that we can
      reach very well de novo identification results. Finally, we show how to count the number of glycan
      topologies for a fixed size or a fixed mass. We generalize this result to count the number of
      (labeled) trees with bounded out degree, improving on results obtained using P{\'o}lya's
      enumeration theorem.},
     author = {S. B{\"o}cker and B. Kehr and F. Rasche},
     journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
     month = {July},
     number = {4},
     pages = {976--986},
     publisher = {IEEE computer society, TCBB},
     title = {Determination of Glycan Structure from Tandem Mass Spectra},
     url = {http://publications.imp.fu-berlin.de/1132/},
     volume = {8},
     year = {2011}
    }
  • T. Rausch, K. Reinert, L. S. Heath, N. Ramakrishnan, “Practical multiple Sequence alignment”, p. 347, 2011.
    cite this publication
    @incollection{fu_mi_publications393,
     abstract = {Abstract Multiple sequence alignment as a means of comparing DNA, RNA or amino acid
      sequences is an essential precondition for various analyses, including structure prediction,
      modeling binding sites, phylogeny or function prediction. This range of applications implies a
      demand for versatile, flexible and specialized meth- ods to compute accurate alignments. This
      chapter summarizes the key algorithmic insights gained in the past years to facilitate both, an
      easy understanding of the current multiple sequence alignment literature and to enable the readers
      to use and apply current tools in their own everyday research.},
     author = {T. Rausch and K. Reinert},
     booktitle = {Problem Solving Handbook in Computational Biology and Bioinformatics},
     editor = {L. S. Heath and N. Ramakrishnan},
     pages = {21--43},
     publisher = {Springer Science+Business Media},
     title = {Practical multiple Sequence alignment},
     url = {http://publications.imp.fu-berlin.de/393/},
     year = {2011}
    }

2010

  • Tobias Rausch, “Dissecting multiple sequence alignment methods”, 2010-06-08.
    cite this publication
    @phdthesis{fu_mi_publications2522,
     abstract = {Multiple sequence alignments are an indispensable tool in bioinformatics. Many
      applications rely on accurate multiple alignments, including protein structure prediction,
      phylogeny and the modeling of binding sites. In this thesis we dissected and analyzed the crucial
      algorithms and data structures required to construct such a multiple alignment. Based upon that
      dissection, we present a novel graph-based multiple sequence alignment program and a new method
      for multi-read alignments occurring in assembly projects. The advantage of the graph-based
      alignment is that a single vertex can represent a single character, a large segment or even an
      abstract entity such as a gene. This gives rise to the opportunity to apply the consistency-based
      progressive alignment paradigm to alignments of genomic sequences. The proposed multi-read
      alignment method outperforms similar methods in terms of alignment quality and it is apparently
      one of the first methods that can readily be used for insert sequencing. An important aspect of
      this thesis was the design, the development and the integration of the essential multiple sequence
      alignment components in the SeqAn library. SeqAn is a software library for sequence analysis that
      provides the core algorithmic components required to analyze large-scale sequence data. SeqAn aims
      at bridging the current gap between algorithm theory and available practical implementations in
      bioinformatics. Hence, we always describe in conjunction to the theoretical development of the
      methods, the actual implementation of the data structures and algorithms in order to strengthen
      the use of SeqAn as an experimental platform for rapidly developing and testing applications. All
      presented methods are part of the open source SeqAn library that can be downloaded from our
      website, www.seqan.de.},
     author = {Tobias Rausch},
     month = {June},
     school = {Freie Universit{\"a}t Berlin},
     title = {Dissecting multiple sequence alignment methods},
     url = {http://publications.imp.fu-berlin.de/2522/},
     year = {2010}
    }
  • A.-K. Emde, M. Grunert, D. Weese, K. Reinert, S. R. Sperling, “MicroRazerS: Rapid alignment of small RNA reads”, vol. 26, iss. 1, 2010-01-01.
    cite this publication
    @article{fu_mi_publications792,
     abstract = {Motivation: Deep sequencing has become the method of choice for determining the small
      RNA content of a cell. Mapping the sequenced reads onto their reference genome serves as the basis
      for all further analyses, namely for identification and quantification. A method frequently used
      is Mega BLAST followed by several filtering steps, even though it is slow and inefficient for this
      task. Also, none of the currently available short read aligners has established itself for the
      particular task of small RNA mapping. Results: We present MicroRazerS, a tool optimized for
      mapping small RNAs onto a reference genome. It is an order of magnitude faster than Mega BLAST and
      comparable in speed to other short read mapping tools. In addition, it is more sensitive and easy
      to handle and adjust. Availability: MicroRazerS is part of the SeqAn C++ library and can be
      downloaded from http://www.seqan.de/projects/MicroRazerS.html. Contact: emde@inf.fu-berlin.de,
      grunert@molgen.mpg.de},
     author = {A.-K. Emde and M. Grunert and D. Weese and K. Reinert and S. R. Sperling},
     journal = {Bioinformatics},
     month = {January},
     number = {1},
     pages = {123--124},
     publisher = {Oxford University Press},
     title = {MicroRazerS: Rapid alignment of small RNA reads},
     url = {http://publications.imp.fu-berlin.de/792/},
     volume = {26},
     year = {2010}
    }
  • A. Gogol-Döring, K. Reinert, “Biological Sequence Analysis using the SeqAn C++ Library”, iss. 1, p. 311, 2010.
    cite this publication
    @book{fu_mi_publications825,
     abstract = {Before the SeqAn project, there was clearly a lack of available implementations in
      sequence analysis, even for standard tasks. Implementations of needed algorithmic components were
      either unavailable or hard to access in third-party monolithic software products. Addressing these
      concerns, the developers of SeqAn created a comprehensive, easy-to-use, open source C++ library of
      efficient algorithms and data structures for the analysis of biological sequences. Written by the
      founders of this project, Biological Sequence Analysis Using the SeqAn C++ Library covers the
      SeqAn library, its documentation, and the supporting infrastructure. The first part of the book
      describes the general library design. It introduces biological sequence analysis problems,
      discusses the benefit of using software libraries, summarizes the design principles and goals of
      SeqAn, details the main programming techniques used in SeqAn, and demonstrates the application of
      these techniques in various examples. Focusing on the components provided by SeqAn, the second
      part explores basic functionality, sequence data structures, alignments, pattern and motif
      searching, string indices, and graphs. The last part illustrates applications of SeqAn to genome
      alignment, consensus sequence in assembly projects, suffix array construction, and more. This
      handy book describes a user-friendly library of efficient data types and algorithms for sequence
      analysis in computational biology. SeqAn enables not only the implementation of new algorithms,
      but also the sound analysis and comparison of existing algorithms.},
     address = {Boca Raton, USA},
     author = {A. Gogol-D{\"o}ring and K. Reinert},
     number = {1},
     publisher = {CRC Press},
     series = {Chapman \& Hall/CRC Mathematical \& Computational Biology},
     title = {Biological Sequence Analysis using the SeqAn C++ Library},
     url = {http://publications.imp.fu-berlin.de/825/},
     year = {2010}
    }
  • C. Bielow, S. Ruzek, C. Huber, K. Reinert, “Optimal Decharging and Clustering of Charge Ladders Generated in ESI−MS”, vol. 9, iss. 5, 2010-03-04.
    cite this publication
    @article{fu_mi_publications895,
     abstract = {In electrospray ionization mass spectrometry (ESI?MS), peptide and protein ions are
      usually observed in multiple charge states. Moreover, adduction of the multiply charged species
      with other ions frequently results in quite complex signal patterns for a single analyte, which
      significantly complicates the derivation of quantitative information from the mass spectra.
      Labeling strategies targeting the MS1 level further aggravate this situation, as multiple
      biological states such as healthy or diseased must be represented simultaneously. We developed an
      integer linear programming (ILP) approach, which can cluster signals belonging to the same peptide
      or protein. The algorithm is general in that it models all possible shifts of signals along the
      m/z axis. These shifts can be induced by different charge states of the compound, the presence of
      adducts (e.g., potassium or sodium), and/or a fixed mass label (e.g., from ICAT or nicotinic acid
      labeling), or any combination of the above. We show that our approach can be used to infer more
      features in labeled data sets, correct wrong charge assignments even in high-resolution MS,
      improve mass precision, and cluster charged species in different charge states and several adduct
      types.},
     author = {C. Bielow and S. Ruzek and C. Huber and K. Reinert},
     journal = {J. Proteome Res.},
     month = {March},
     note = {online publication complete, printed publication to be expected},
     number = {5},
     pages = {2688--2695},
     publisher = {ACS Publications},
     title = {Optimal Decharging and Clustering of Charge Ladders Generated in ESI?MS},
     url = {http://publications.imp.fu-berlin.de/895/},
     volume = {9},
     year = {2010}
    }
  • M. Birn, M. Holtgrewe, P. Sanders, J. Singler, “Simple and Fast Nearest Neighbor Search”, 2010.
    cite this publication
    @article{fu_mi_publications926,
     abstract = {We present a simple randomized data structure for two-dimensional point sets that
      allows fast nearest neighbor queries in many cases. An implementation outperforms several previous
      implementations for commonly used benchmarks.},
     author = {M. Birn and M. Holtgrewe and P. Sanders and J. Singler},
     journal = {2010 Proceedings of the Twelfth Workshop on Algorithm Engineering and Experiments
      (ALENEX)},
     pages = {43--54},
     publisher = {ACM SIAM},
     title = {Simple and Fast Nearest Neighbor Search},
     url = {http://publications.imp.fu-berlin.de/926/},
     year = {2010}
    }
  • M. Holtgrewe, P. Sanders, C. Schulz, “Engineering a scalable high quality graph partitioner”, 2010-04.
    cite this publication
    @article{fu_mi_publications930,
     abstract = {We describe an approach to parallel graph partitioning that scales to hundreds of
      processors and produces a high solution quality. For example, for many instances from Walshaw's
      benchmark collection we improve the best known partitioning. We use the well known framework of
      multi-level graph partitioning. All components are implemented by scalable parallel algorithms.
      Quality improvements compared to previous systems are due to better prioritization of edges to be
      contracted, better approximation algorithms for identifying matchings, better local search
      heuristics, and perhaps most notably, a parallelization of the FM local search algorithm that
      works more locally than previous approaches.},
     author = {M. Holtgrewe and P. Sanders and C. Schulz},
     journal = {2010 IEEE International Symposium on Parallel \& Distributed Processing (IPDPS)},
     month = {April},
     pages = {1--12},
     title = {Engineering a scalable high quality graph partitioner},
     url = {http://publications.imp.fu-berlin.de/930/},
     year = {2010}
    }
  • D. HĂŒser, A. Gogol-Döring, T. Lutter, S. Weger, K. Winter, E.-M. Hammer, T. Cathomen, K. Reinert, R. Heilbronn, “Integration Preferences of Wildtype AAV-2 for Consensus Rep-Binding Sites at Numerous Loci in the Human Genome”, vol. 6, iss. 7, 2010-07-08.
    cite this publication
    @article{fu_mi_publications935,
     abstract = {Adeno-associated virus type 2 (AAV) is known to establish latency by preferential
      integration in human chromosome 19q13.42. The AAV non-structural protein Rep appears to target a
      site called AAVS1 by simultaneously binding to Rep-binding sites (RBS) present on the AAV genome
      and within AAVS1. In the absence of Rep, as is the case with AAV vectors, chromosomal integration
      is rare and random. For a genome-wide survey of wildtype AAV integration a
      linker-selection-mediated (LSM)-PCR strategy was designed to retrieve AAV-chromosomal junctions.
      DNA sequence determination revealed wildtype AAV integration sites scattered over the entire human
      genome. The bioinformatic analysis of these integration sites compared to those of rep-deficient
      AAV vectors revealed a highly significant overrepresentation of integration events near to
      consensus RBS. Integration hotspots included AAVS1 with 10\% of total events. Novel hotspots near
      consensus RBS were identified on chromosome 5p13.3 denoted AAVS2 and on chromsome 3p24.3 denoted
      AAVS3. AAVS2 displayed seven independent junctions clustered within only 14 bp of a consensus RBS
      which proved to bind Rep in vitro similar to the RBS in AAVS3. Expression of Rep in the presence
      of rep-deficient AAV vectors shifted targeting preferences from random integration back to the
      neighbourhood of consensus RBS at hotspots and numerous additional sites in the human genome. In
      summary, targeted AAV integration is not as specific for AAVS1 as previously assumed. Rather, Rep
      targets AAV to integrate into open chromatin regions in the reach of various, consensus RBS
      homologues in the human genome.},
     author = {D. H{\"u}ser and A. Gogol-D{\"o}ring and T. Lutter and S. Weger and K. Winter and E.-M.
      Hammer and T. Cathomen and K. Reinert and R. Heilbronn},
     journal = {PLoS Pathogens},
     month = {July},
     number = {7},
     pages = {e1000985},
     title = {Integration Preferences of Wildtype AAV-2 for Consensus Rep-Binding Sites at Numerous Loci
      in the Human Genome},
     url = {http://publications.imp.fu-berlin.de/935/},
     volume = {6},
     year = {2010}
    }
  • M. Holtgrewe, “Mason – A Read Simulator for Second Generation Sequencing Data”, 2010-10.
    cite this publication
    @article{fu_mi_publications962,
     abstract = {We present a read simulator software for Illumina, 454 and Sanger reads. Its features
      include position specific error rates and base quality values. For Illumina reads, we give a
      comprehensive analysis with empirical data for the error and quality model. For the other
      technologies, we use models from the literature. It has been written with performance in mind and
      can sample reads from large genomes. The C++ source code is extensible, and freely available under
      the GPL/LGPL.},
     author = {M. Holtgrewe},
     journal = {Technical Report FU Berlin},
     month = {October},
     title = {Mason ? A Read Simulator for Second Generation Sequencing Data},
     url = {http://publications.imp.fu-berlin.de/962/},
     year = {2010}
    }

2009

  • Ole Schulz-Trieglaff, “Computational methods for Quantitative Peptide Mass Spectrometry”, 2009-08-05.
    cite this publication
    @phdthesis{fu_mi_publications2534,
     abstract = {This thesis presents algorithms for the analysis of liquid chromatography-mass
      spectrometry (LC-MS) data. Mass spectrometry is a technology that can be used to determine the
      identities and abundances of the compounds in complex samples. In combination with liquid
      chromatography, it has become a popular method in the field of proteomics, the large-scale study
      of proteins and peptides in living systems. This area of research has gained a lot of interest in
      recent years since proteins control fundamental reactions in the cell. Consequently, a deeper
      knowledge of their function is expected to be crucial for the development of new drugs and the
      cure of diseases. The data sets obtained from an LC-MS experiment are large and highly complex.
      The outcome of such an experiment is called an LC-MS map. The map is a collection of mass spectra.
      They contain, among the signals of interest, a high amount of noise and other disturbances. That
      is why algorithms for the low-level processing of LC-MS data are becoming increasingly important.
      These algorithms are the focus of this text. Our novel contributions are threefold: first, we
      introduce SweepWavelet, an algorithm for the efficient detection and quantification of peptides
      from LC-MS data. The quantification of proteins and peptides using mass spectrometry is of high
      interest for biomedical research but also for the pharmaceutical industry since it is usually
      among the first steps in an LC-MS data analysis pipeline and all subsequent steps depend on its
      quality. Our approach was among the first to address this problem in a sound computational
      framework. It consists of three steps: first, we apply a tailored wavelet function that filters
      mass spectra for the isotope peaks of peptides. Second, we use a method inspired by the sweep-line
      paradigm which makes use of the redundant information in LC-MS data to determine mass, charge,
      retention time and abundance of all peptides. Finally, we apply a flexible peptide signal model to
      filter the extracted signals for false positives. The second part of this thesis deals with the
      benchmarking of LC-MS signal detection algorithms. This is a non-trivial task since it is
      difficult to establish a ground truth using real world samples: which sample compounds become
      visible in an LC-MS data set is not known in advance. To this end, we use annotated data and
      simulations to assess the performance of currently available algorithms. To simulate benchmark
      data, we developed a simulation software called LC-MSsim. It incorporates computational models for
      retention time prediction, peptide detectability, isotope pattern and elution peaks. Using this
      software, we can simulate all steps in an LC-MS experiment and obtain a list with the positions,
      charges and abundances of all peptide signals contained in the resulting LC-MS map. This gives us
      a ground truth against which we can match the results of a signal detection algorithm. In this
      thesis, we use it for the benchmarking of quantification algorithms but its scope is wider and it
      can also be used to evaluate other algorithms. To our knowledge, LC-MSsim is the first software
      that can simulate the full LC-MS data acquisition process. The third contribution of this thesis
      is a statistical framework for the quality assessment of quantitative LC-MS experiments. Whereas
      quality assessment and control are already widespread in the field of gene expression analysis,
      our work is the first to address this problem for LCMS data. We use methods from robust statistics
      to detect outlier LC-MS maps in large-scale quantitative experiments. Our approach introduces the
      notion of quality descriptors to derive an abstract representation of an LC-MS map and applies a
      robust principal component analysis based on projection pursuit. We show that it is sensible to
      use robust statistics for this problem and evaluate our method on simulated maps and on data from
      three real-world LC-MS studies.},
     author = {Ole Schulz-Trieglaff},
     month = {August},
     school = {Freie Universit{\"a}t Berlin},
     title = {Computational methods for Quantitative Peptide Mass Spectrometry},
     url = {http://publications.imp.fu-berlin.de/2534/},
     year = {2009}
    }
  • Andreas Gogol-Döring, “SeqAn”, 2009-11-26.
    cite this publication
    @phdthesis{fu_mi_publications2542,
     abstract = {SeqAn is a library of efficient algorithms and data structures for sequence analysis,
      which means processing large amounts of biomedical data like DNA or proteine sequences. The
      library was developed for two groups of users: Software engineers can use it for the
      implementation of new software tools. Such tools are essential for biological and medical
      research. Algorithm designers may also use the library as a platform for the development, testing
      and comparison of algorithms. The project therefore contributes to bioinformatics engineering with
      the eventual purpose to promote the scientific research in life science.},
     author = {Andreas Gogol-D{\"o}ring},
     month = {November},
     school = {Freie Universit{\"a}t Berlin},
     title = {SeqAn},
     url = {http://publications.imp.fu-berlin.de/2542/},
     year = {2009}
    }
  • T. Rausch, S. Koren, G. Denisov, D. Weese, A.-K. Emde, A. Döring, K. Reinert, “A consistency-based consensus algorithm for de novo and reference-guided sequence assembly of short reads”, vol. 25, iss. 9, 2009.
    cite this publication
    @article{fu_mi_publications392,
     abstract = {Motivation: Novel high-throughput sequencing technologies pose new algorithmic
      challenges in handling massive amounts of short- read, high-coverage data. A robust and versatile
      consensus tool is of particular interest for such data since a sound multi-read alignment is a
      prerequisite for variation analyses, accurate genome assemblies and insert sequencing. Results: A
      multi-read alignment algorithm for de novo or reference- guided genome assembly is presented. The
      program identifies segments shared by multiple reads and then aligns these segments using a
      consistency-enhanced alignment graph. On real de novo sequencing data obtained from the newly
      established NCBI Short Read Archive, the program performs similarly in quality to other comparable
      programs. On more challenging simulated datasets for insert sequencing and variation analyses, our
      program outperforms the other tools. Availability: The consensus program can be downloaded from
      http://www.seqan.de/projects/consensus.html. It can be used stand- alone or in conjunction with
      the Celera Assembler. Both application scenarios as well as the usage of the tool are described in
      the documentation. Contact: rausch@inf.fu-berlin.de},
     author = {T. Rausch and S. Koren and G. Denisov and D. Weese and A.-K. Emde and A. D{\"o}ring and
      K. Reinert},
     journal = {Bioinformatics},
     number = {9},
     pages = {1118--1124},
     publisher = {Oxford University Press},
     title = {A consistency-based consensus algorithm for de novo and reference-guided sequence assembly
      of short reads},
     url = {http://publications.imp.fu-berlin.de/392/},
     volume = {25},
     year = {2009}
    }
  • R. A. Bauer, K. Rother, P. Moor, K. Reinert, T. Steinke, J. M. Bujnicki, R. Preissner, “Fast Structural Alignment of Biomolecules Using a Hash Table, N-Grams and String Descriptors”, vol. 2, iss. 2, 2009.
    cite this publication
    @article{fu_mi_publications450,
     abstract = {This work presents a generalized approach for the fast structural alignment of
      thousands of macromolecular structures. The method uses string representations of a macromolecular
      structure and a hash table that stores n-grams of a certain size for searching. To this end,
      macromolecular structure-to-string translators were implemented for protein and RNA structures. A
      query against the index is performed in two hierarchical steps to unite speed and precision. In
      the ?rst step the query structure is translated into n-grams, and all target structures containing
      these n-grams are retrieved from the hash table. In the second step all corresponding n-grams of
      the query and each target structure are subsequently aligned, and after each alignment a score is
      calculated based on the matching n-grams of query and target. The extendable framework enables the
      user to query and structurally align thousands of protein and RNA structures on a commodity
      machine and is available as open source from http://la jolla.sf.net.},
     author = {R. A. Bauer and K. Rother and P. Moor and K. Reinert and T. Steinke and J. M. Bujnicki
      and R. Preissner},
     journal = {Algorithms and Molecular Sciences},
     number = {2},
     pages = {692--709},
     publisher = {MDPI},
     title = {Fast Structural Alignment of Biomolecules Using a Hash Table, N-Grams and String
      Descriptors},
     url = {http://publications.imp.fu-berlin.de/450/},
     volume = {2},
     year = {2009}
    }
  • D. Weese, A.-K. Emde, T. Rausch, A. Döring, K. Reinert, “RazerS - Fast Read Mapping with Sensitivity Control”, vol. 19, iss. 9, 2009-07-10.
    cite this publication
    @article{fu_mi_publications453,
     abstract = {Second-generation sequencing technologies deliver DNA sequence data at unprecedented
      high throughput. Common to most biological applications is a mapping of the reads to an almost
      identical or highly similar reference genome. Due to the large amounts of data, e?cient algorithms
      and implementations are crucial for this task. We present an e?cient read mapping tool called
      RazerS. It allows the user to align sequencing reads of arbitrary length using either the Hamming
      distance or the edit distance. Our tool can work either lossless or with a user-de?ned loss rate
      at higher speeds. Given the loss rate, we present an approach that guarantees not to lose more
      reads than speci?ed. This enables the user to adapt to the problem at hand and provides a seamless
      tradeo? between sensitivity and running time.},
     author = {D. Weese and A.-K. Emde and T. Rausch and A. D{\"o}ring and K. Reinert},
     journal = {Genome Research},
     month = {July},
     number = {9},
     pages = {1646--1654},
     title = {RazerS - Fast Read Mapping with Sensitivity Control},
     url = {http://publications.imp.fu-berlin.de/453/},
     volume = {19},
     year = {2009}
    }
  • A. Zerck, E. Nordhoff, A. Reseman, E. Mirgorodskaya, D. Suckau, K. Reinert, H. Lehrach, J. Gobom, “An iterative strategy for precursor ion selection for LC-MS/MS based shotgun proteomics”, 2009-04-30.
    cite this publication
    @article{fu_mi_publications456,
     abstract = {Currently, the precursor ion selection strategies in LC-MS mainly choose the most
      prominent peptide signals for MS/MS analysis. Consequently, high abundant proteins are identified
      by MS/MS of many peptides whereas proteins of lower abundance might elude identification. We
      present a novel, iterative and result-driven approach for precursor ion selection that
      significantly increases the efficiency of an MS/MS analysis by decreasing data redundancy and
      analysis time. By simulating different strategies for precursor ion selection on an existing
      dataset we compare our method to existing result-driven strategies and evaluate its performance
      with regard to mass accuracy, database size, and sample complexity.},
     author = {A. Zerck and E. Nordhoff and A. Reseman and E. Mirgorodskaya and D. Suckau and K. Reinert
      and H. Lehrach and J. Gobom},
     journal = {Journal of Proteome Research},
     month = {April},
     publisher = {American Chemical Society},
     title = {An iterative strategy for precursor ion selection for LC-MS/MS based shotgun proteomics},
     url = {http://publications.imp.fu-berlin.de/456/},
     year = {2009}
    }

2008

  • Eva Lange, “Analysis of mass spectrometric data - peak picking and map alignment”, 2008-09-09.
    cite this publication
    @phdthesis{fu_mi_publications2528,
     abstract = {We study two fundamental processing steps in mass spectrometric data analysis from a
      theoretical and practical point of view. For the detection and extraction of mass spectral peaks
      we developed an efficient peak picking algorithm that is independent of the underlying machine or
      ionization method, and is able to resolve highly convoluted and asymmetric signals. The method
      uses the multiscale nature of spectrometric data by first detecting the mass peaks in the
      wavelet-transformed signal before a given asymmetric peak function is fitted to the raw data. In
      two optional stages, highly overlapping peaks can be separated or all peak parameters can be
      further improved using techniques from nonlinear optimization. In contrast to currently
      established techniques, our algorithm is able to separate overlapping peaks of multiply charged
      peptides in LC-ESI-MS data of low resolution. Furthermore, applied to high-quality MALDI-TOF
      spectra it yields a high degree of accuracy and precision and compares very favorably with the
      algorithms supplied by the vendor of the mass spectrometers. On the high-resolution MALDI spectra
      as well as on the low-resolution LC-MS data set, our algorithm achieves a fast runtime of only a
      few seconds. Another important processing step that can be found in every typical protocol for
      labelfree quantification is the combination of results from multiple LC-MS experiments to improve
      confidence in the obtained measurements or to compare results from different samples. To do so, a
      multiple alignment of the LC-MS maps needs to be estimated. The alignment has to correct for
      variations in mass and elution time which are present in all mass spectrometry experiments. For
      the first time we formally define the multiple LC-MS raw and feature map alignment problem using
      our own distance function for LC-MS maps. Furthermore, we present a solution to this problem. Our
      novel algorithm aligns LC-MS samples and matches corresponding ion species across samples. In a
      first step, it uses an adapted pose clustering approach to efficiently superimpose raw maps as
      well as feature maps. This is done in a star-wise manner, where the elements of all maps are
      transformed onto the coordinate system of a reference map. To detect and combine corresponding
      features in multiple feature maps into a so-called consensus map, we developed an additional step
      based on techniques from computational geometry. We show that our alignment approach is fast and
      reliable as compared to five other alignment approaches. Furthermore, we prove its robustness in
      the presence of noise and its ability to accurately align samples with only few common ion
      species.},
     author = {Eva Lange},
     month = {September},
     school = {Freie Universit{\"a}t Berlin},
     title = {Analysis of mass spectrometric data - peak picking and map alignment},
     url = {http://publications.imp.fu-berlin.de/2528/},
     year = {2008}
    }
  • T. O. F. Conrad, “New statistical algorithms for the analysis of mass spectrometry time-of- flight mass data with applications in clinical diagnostics”, 2008-10-01.
    cite this publication
    @phdthesis{fu_mi_publications2543,
     abstract = {Mass spectrometry (MS) based techniques have emerged as a standard for large- scale
      protein analysis. The ongoing progress in terms of more sensitive machines and improved data
      analysis algorithms led to a constant expansion of its fields of applications. Recently, MS was
      introduced into clinical proteomics with the prospect of early disease detection using proteomic
      pattern matching. Analyzing biological samples (e.g. blood) by mass spectrometry generates mass
      spectra that represent the components (molecules) contained in a sample as masses and their
      respective relative concentrations. In this work, we are interested in those components that are
      constant within a group of individuals but differ much between individuals of two distinct groups.
      These distinguishing components that dependent on a particular medical condition are generally
      called biomarkers. Since not all biomarkers found by the algorithms are of equal (discriminating)
      quality we are only interested in a small biomarker subset that - as a combination - can be used
      as a fingerprint for a disease. Once a fingerprint for a particular disease (or medical condition)
      is identified, it can be used in clinical diagnostics to classify unknown spectra. In this thesis
      we have developed new algorithms for automatic extraction of disease specific fingerprints from
      mass spectrometry data. Special emphasis has been put on designing highly sensitive methods with
      respect to signal detection. Thanks to our statistically based approach our methods are able to
      detect signals even below the noise level inherent in data acquired by common MS machines, such as
      hormones. To provide access to these new classes of algorithms to collaborating groups we have
      created a web-based analysis platform that provides all necessary interfaces for data transfer,
      data analysis and result inspection. To prove the platform's practical relevance it has been
      utilized in several clinical studies two of which are presented in this thesis. In these studies
      it could be shown that our platform is superior to commercial systems with respect to fingerprint
      identification. As an outcome of these studies several fingerprints for different cancer types
      (bladder, kidney, testicle, pancreas, colon and thyroid) have been detected and validated. The
      clinical partners in fact emphasize that these results would be impossible with a less sensitive
      analysis tool (such as the currently available systems). In addition to the issue of reliably
      finding and handling signals in noise we faced the problem to handle very large amounts of data,
      since an average dataset of an individual is about 2.5 Gigabytes in size and we have data of
      hundreds to thousands of persons. To cope with these large datasets, we developed a new framework
      for a heterogeneous (quasi) ad-hoc Grid - an infrastructure that allows to integrate thousands of
      computing resources (e.g. Desktop Computers, Computing Clusters or specialized hardware, such as
      IBM's Cell Processor in a Playstation 3).},
     author = {T. O. F. Conrad},
     month = {October},
     school = {Freie Universit{\"a}t Berlin},
     title = {New statistical algorithms for the analysis of mass spectrometry time-of- flight mass data
      with applications in clinical diagnostics},
     url = {http://publications.imp.fu-berlin.de/2543/},
     year = {2008}
    }
  • Markus Johann Bauer, “A combinatorial approach to RNA sequence-structure alignments”, 2008-07-30.
    cite this publication
    @phdthesis{fu_mi_publications2545,
     abstract = {Until a couple of years ago the scientific mainstream held that genetic information,
      stored as DNA strands, is transcribed to RNA, and RNA sequences are in turn translated to
      proteins, the actual functional units in the cell. RNA was generally believed to be a helper
      molecule in the cell until the beginning of the new millennium. This view changed. We see the
      potential of RNA as one of the key cellular players. In this thesis we present a novel framework
      for computing sequence-structure alignments of RNA sequences. Our contribution is twofold: first,
      we give a graph-theoretic model for the computation of multiple sequence-structure alignments. We
      phrase the model as an integer linear program (ILP) and show how we can relax the ILP such that we
      are able to compute optimal or near-optimal solutions for the original problem. In a subsequent
      step, we augment the initial model with stacking energies. Stacking base pairs greatly contribute
      to the energetic stability of the overall structure and should therefore be additionally rewarded.
      We extend the original ILP such that stacking energies are incorporated. Second, we give extensive
      computational results on real data from the RFAM database. We compare the performance of truly
      multiple sum-of-pairs sequence-structure alignments to heuristic sequence-structure alignments. We
      show that the objective function value of the sum-of-pairs model is generally higher compared to
      the heuristically inferred alignments. At the same time, we sketch the computational limits for
      the sum-of-pairs multiple sequence-structure model. The computational costs for computing exact
      multiple sequence-structure alignments are generally very high. To validate our approach on a
      larger test set, we run two implementations that take two sequences as their input. LaRA and
      SLaRA---based on the initial and the stack model---compute all pairwise sequence-structure
      alignments and use the external program TCOFFEE to infer a consistency-based multiple
      sequence-structure alignment. Additionally, we run the progressive versions PLaRA and PSLaRA on
      the same input data set. Our experiments on the BRAliBase benchmark set show that our tools are
      top-ranked for all input classes. Furthermore, our implementations need less running time compared
      to similar approaches. Subsequently, we compare two different algorithms for computing the optimal
      value of the Lagrangian dual and show that in our test setting the conceptually easier subgradient
      method is superior to the bundle method. Finally, we incorporate our Lagrangian relaxation
      approach into a branch-and-bound framework. We show for which instances we are able to compute
      provably optimal solutions and compare our results with previously published results of a
      branch-and-bound approach for the related quadratic knapsack problem.},
     author = {Markus Johann Bauer},
     month = {July},
     school = {Freie Universit{\"a}t Berlin},
     title = {A combinatorial approach to RNA sequence-structure alignments},
     url = {http://publications.imp.fu-berlin.de/2545/},
     year = {2008}
    }
  • Abha Singh Bais, “Annotated Alignments”, 2008-08-01.
    cite this publication
    @phdthesis{fu_mi_publications2851,
     abstract = {Elucidating the mechanisms of transcriptional regulation relies heavily on the sequence
      annotation of the binding sites of DNA-binding proteins called transcription factors. With the
      rationale that binding sites conserved across different species are more likely to be functional,
      the standard approach is to employ cross-species comparisons and focus the search to conserved
      regions. Usually, computational methods that annotate conserved binding sites perform the
      alignment and binding site annotation steps separately and combine the results in the end. If the
      binding site descriptions are weak or the sequence similarity is low, the local gap structure of
      the alignment poses a problem in detecting the conserved sites. In this thesis, I introduce a
      novel method that integrates the two axes of sequence conservation and binding site annotation in
      a simultaneous approach yielding {$\backslash$}emph\{annotated alignments\} -- pairwise alignments
      with parts annotated as putative conserved transcription factor binding sites. Standard pairwise
      alignments are extended to include additional states for binding site profiles. A statistical
      framework that estimates profile-related parameters based on desired type I and type II errors is
      prescribed. This forms the core of the tool \{{$\backslash$}bf\{SimAnn\}\}. As an extension, I use
      existing probabilistic models to demonstrate how the framework can be adapted to consider
      position-specific evolutionary characteristics of binding sites during parameter estimation. This
      underlies the tool \{{$\backslash$}bf\{eSimAnn\}\}. Through simulations and real data analysis, I
      study the influence of considering a simultaneous approach as opposed to a multi-step one on
      resulting predictions. The former enables a local rearrangement in the alignment structure to
      bring forth perfectly aligned binding sites. This precludes the necessity of adopting
      post-processing steps to handle errors in pre-computed alignments, as is usually done in
      multi-step approaches. Additionally, the framework for parameter estimation is applicable to any
      novel profile of interest. Especially for instances with poor sequence conservation or profile
      quality, the simultaneous approach stands out. As a by-product of the analysis, I also present a
      formulation of the annotated alignment problem as an extended pair Hidden Markov Model and
      illustrate the correspondence between the various theoretical concepts.},
     author = {Abha Singh Bais},
     month = {August},
     school = {Freie Universit{\"a}t Berlin},
     title = {Annotated Alignments},
     url = {http://publications.imp.fu-berlin.de/2851/},
     year = {2008}
    }
  • M. Bauer, G. W. Klau, K. Reinert, “An Exact Mathematical Programming Approach to Multiple RNA Sequence-Structure Alignment.”, 2008.
    cite this publication
    @article{fu_mi_publications331,
     author = {M. Bauer and G. W. Klau and K. Reinert},
     journal = {Algorithmic Operations Research},
     note = {to appear},
     title = {An Exact Mathematical Programming Approach to Multiple RNA Sequence-Structure Alignment.},
     url = {http://publications.imp.fu-berlin.de/331/},
     year = {2008}
    }
  • M. Bodirsky, C. Gröpl, M. Kang, “Generating unlabeled connected cubic planar graphs uniformly at random”, vol. 32, iss. 2, 2008.
    cite this publication
    @article{fu_mi_publications338,
     abstract = {We present an expected polynomial time algorithm to generate an unlabeled connected
      cubic planar graph uniformly at random. We first consider rooted connected cubic planar graphs,
      i.e., we count connected cubic planar graphs up to isomorphisms that fix a certain directed edge.
      Based on decompositions along the connectivity structure, we derive recurrence formulas for the
      exact number of rooted cubic planar graphs. This leads to rooted 3-connected cubic planar graphs,
      which have a unique embedding on the sphere. Special care has to be taken for rooted graphs that
      have a sense-reversing automorphism. Therefore we introduce the concept of colored networks, which
      stand in bijective correspondence to rooted 3-connected cubic planar graphs with given symmetries.
      Colored networks can again be decomposed along the connectivity structure. For rooted 3-connected
      cubic planar graphs embedded in the plane, we switch to the dual and count rooted triangulations.
      Since all these numbers can be evaluated in polynomial time using dynamic programming, rooted
      connected cubic planar graphs can be generated uniformly at random in polynomial time by inverting
      the decomposition along the connectivity structure. To generate connected cubic planar graphs
      without a root uniformly at random, we apply rejection sampling and obtain an expected polynomial
      time algorithm},
     author = {M. Bodirsky and C. Gr{\"o}pl and M. Kang},
     journal = {Random Structures and Algorithms},
     number = {2},
     pages = {157--180},
     title = {Generating unlabeled connected cubic planar graphs uniformly at random},
     url = {http://publications.imp.fu-berlin.de/338/},
     volume = {32},
     year = {2008}
    }
  • E. Lange, R. Tautenhahn, S. Neumann, C. Gröpl, “Critical assessment of alignment procedures for LC-MS proteomics and metabolomic measurements”, vol. 9, iss. 375, 2008.
    cite this publication
    @article{fu_mi_publications379,
     author = {E. Lange and R. Tautenhahn and S. Neumann and C. Gr{\"o}pl},
     journal = {BMC Bioinformatics},
     number = {375},
     title = {Critical assessment of alignment procedures for LC-MS proteomics and metabolomic
      measurements},
     url = {http://publications.imp.fu-berlin.de/379/},
     volume = {9},
     year = {2008}
    }
  • T. Rausch, A.-K. Emde, K. Reinert, “Robust consensus computation”, vol. 9, iss. Suppl 10, 2008.
    cite this publication
    @article{fu_mi_publications390,
     author = {T. Rausch and A.-K. Emde and K. Reinert},
     journal = {BMC Bioinformatics},
     number = {Suppl 10},
     pages = {P4},
     title = {Robust consensus computation},
     url = {http://publications.imp.fu-berlin.de/390/},
     volume = {9},
     year = {2008}
    }
  • T. Rausch, A.-K. Emde, D. Weese, C. Notredame, K. Reinert, “Segment-based multiple sequence alignment”, vol. 24, iss. 16, 2008.
    cite this publication
    @article{fu_mi_publications391,
     abstract = {Motivation: Many multiple sequence alignment tools have been developed in the past,
      progressing either in speed or alignment accuracy. Given the importance and wide-spread use of
      alignment tools, progress in both categories is a contribution to the community and has driven
      research in the field so far. Results: We introduce a graph-based extension to the
      consistency-based, progressive alignment strategy. We apply the consistency notion to segments
      instead of single characters. The main problem we solve in this context is to define segments of
      the sequences in such a way that a graph-based alignment is possible. We implemented the algorithm
      using the SeqAn library and report results on amino acid and DNA sequences. The benefit of our
      approach is threefold: (1) sequences with conserved blocks can be rapidly aligned, (2) the
      implementation is conceptually easy, generic and fast and (3) the consistency idea can be extended
      to align multiple genomic sequences. Availability: The segment-based multiple sequence alignment
      tool can be downloaded from http://www.seqan.de/projects/msa.html. A novel version of T-Coffee
      interfaced with the tool is available from http://www.tcoffee.org. The usage of the tool is
      described in both documentations. Contact: rausch@inf.fu-berlin.de},
     author = {T. Rausch and A.-K. Emde and D. Weese and C. Notredame and K. Reinert},
     journal = {Bioinformatics},
     number = {16},
     pages = {i187--192},
     title = {Segment-based multiple sequence alignment},
     url = {http://publications.imp.fu-berlin.de/391/},
     volume = {24},
     year = {2008}
    }
  • T. Rausch, A. Thomas, N. J. Camp, L. A. Facelli, “A parallel genetic algorithm to discover patterns in genetic markers that indicate predisposition to multifactorial disease”, vol. 38, 2008-07.
    cite this publication
    @article{fu_mi_publications394,
     abstract = {This paper describes a novel algorithm to analyze genetic linkage data using pattern
      recognition techniques and genetic algorithms (GA). The method allows a search for regions of the
      chromosome that may contain genetic variations that jointly predispose individuals for a
      particular disease. The method uses correlation analysis, filtering theory and genetic algorithms
      to achieve this goal. Because current genome scans use from hundreds to hundreds of thousands of
      markers, two versions of the method have been implemented. The first is an exhaustive analysis
      version that can be used to visualize, explore, and analyze small genetic data sets for two marker
      correlations; the second is a GA version, which uses a parallel implementation allowing searches
      of higher-order correlations in large data sets. Results on simulated data sets indicate that the
      method can be informative in the identification of major disease loci and gene{\^a}??gene
      interactions in genome-wide linkage data and that further exploration of these techniques is
      justified. The results presented for both variants of the method show that it can help genetic
      epidemiologists to identify promising combinations of genetic factors that might predispose to
      complex disorders. In particular, the correlation analysis of IBD expression patterns might hint
      to possible gene{\^a}??gene interactions and the filtering might be a fruitful approach to
      distinguish true correlation signals from noise.},
     author = {T. Rausch and A. Thomas and N. J. Camp and L. A. Facelli},
     journal = {Comput. Biol. Med.},
     month = {July},
     pages = {826--836},
     title = {A parallel genetic algorithm to discover patterns in genetic markers that indicate
      predisposition to multifactorial disease},
     url = {http://publications.imp.fu-berlin.de/394/},
     volume = {38},
     year = {2008}
    }
  • M. H. Schulz, D. Weese, T. Rausch, A. Döring, K. Reinert, M. Vingron, “Fast and Adaptive Variable Order Markov Chain Construction”, 2008.
    cite this publication
    @inproceedings{fu_mi_publications401,
     abstract = {Variable order Markov chains (VOMCs) are a flexible class of models that extend the
      well-known Markov chains. They have been applied to a variety of problems in computational
      biology, e.g. protein family classification. A linear time and space construction algorithm has
      been published in 2000 by Apostolico and Bejerano. However, neither a report of the actual running
      time nor an implementation of it have ever been published since. Using their theoretical results,
      we implement general and problem oriented algorithms considering recent advances in string
      matching. We introduce a new software which is orders of magnitudes faster than current tools for
      building VOMCs, and is suitable for large scale analysis. Along the way we show that the lazy
      suffix tree algorithm by Giegerich and others can compete with state-of-the-art suffix array
      methods in terms of time and space under the type of constraints we have analyzed in this work.},
     author = {M. H. Schulz and D. Weese and T. Rausch and A. D{\"o}ring and K. Reinert and M. Vingron},
     booktitle = {Proceedings of the 8th International Workshop in Algorithms in Bioinformatics
      (WABI'08)},
     pages = {306--317},
     publisher = {Springer Verlag},
     title = {Fast and Adaptive Variable Order Markov Chain Construction},
     url = {http://publications.imp.fu-berlin.de/401/},
     year = {2008}
    }
  • O. Schulz-Trieglaff, R. Hussong, C. Gröpl, A. Hildebrandt, A. Hildebrandt, Ch. Huber, K. Reinert, “Computational Quantification of Peptides from LC-MS data”, vol. 15, iss. 7, 2008.
    cite this publication
    @article{fu_mi_publications406,
     abstract = {Liquid chromatography coupled to mass spectrometry (LC-MS) has become a major tool for
      the study of biological processes. High-throughput LC-MS experimentsare frequently conducted in
      modern laboratories, generating an enormous amountof data per day. A manual inspection is
      therefore no longer a feasible task. Consequently, there is a need for computational tools that
      can rapidly provide informationabout mass, elution time, and abundance of the compounds in a LC-MS
      sample. Wepresent an algorithm for the detection and quantification of peptides in LC-MS data. Our
      approach is flexible and independent of the MS technology in use. It is basedon a combination of
      the sweep line paradigm with a novel wavelet function tailoredto detect isotopic patterns of
      peptides. We propose a simple voting schema to usethe redundant information in consecutive scans
      for an accurate determination ofmonoisotopic masses and charge states. By explicitly modeling the
      instrument inaccuracy, we are also able to cope with data sets of different quality and
      resolution.We evaluate our technique on data from different instruments and show that we
      canrapidly estimate mass, centroid of retention time and abundance of peptides in a sound
      algorithmic framework. Finally, we compare the performance of our method to several other
      techniques on three data sets of varying complexity.},
     author = {O. Schulz-Trieglaff and R. Hussong and C. Gr{\"o}pl and A. Hildebrandt and A. Hildebrandt
      and Ch. Huber and K. Reinert},
     journal = {Journal of Computational Biology},
     keywords = {computational mass spectrometry, liquid chromatography - massspectrometry,
      quantification, wavelets},
     number = {7},
     pages = {685--704},
     title = {Computational Quantification of Peptides from LC-MS data},
     url = {http://publications.imp.fu-berlin.de/406/},
     volume = {15},
     year = {2008}
    }
  • O. Schulz-Trieglaff, N. Pfeifer, C. Gröpl, O. Kohlbacher, K. Reinert, “LC-MSsim - a simulation software for liquid chromatography mass spectrometry data”, vol. 9, iss. 423, 2008.
    cite this publication
    @article{fu_mi_publications408,
     abstract = {BACKGROUND: Mass Spectrometry coupled to Liquid Chromatography (LC-MS) is commonly used
      to analyze the protein content of biological samples in large scale studies. The data resulting
      from an LC-MS experiment is huge, highly complex and noisy. Accordingly, it has sparked new
      developments in Bioinformatics, especially in the fields of algorithm development, statistics and
      software engineering. In a quantitative label-free mass spectrometry experiment, crucial steps are
      the detection of peptide features in the mass spectra and the alignment of samples by correcting
      for shifts in retention time. At the moment, it is difficult to compare the plethora of algorithms
      for these tasks. So far, curated benchmark data exists only for peptide identification algorithms
      but no data that represents a ground truth for the evaluation of feature detection, alignment and
      filtering algorithms. RESULTS: We present LC-MSsim, a simulation software for LC-ESI-MS
      experiments. It simulates ESI spectra on the MS level. It reads a list of proteins from a FASTA
      file and digests the protein mixture using a user-defined enzyme. The software creates an LC-MS
      data set using a predictor for the retention time of the peptides and a model for peak shapes and
      elution profiles of the mass spectral peaks. Our software also offers the possibility to add
      contaminants, to change the background noise level and includes a model for the detectability of
      peptides in mass spectra. After the simulation, LC-MSsim writes the simulated data to public XML
      formats (mzXML or mzData). The software also stores the positions (monoisotopic m/z and retention
      time) and ion counts of the simulated ions in separate files. CONCLUSIONS: LC-MSsim generates
      simulated LC-MS data sets and incorporates models for peak shapes and contaminations. Algorithm
      developers can match the results of feature detection and alignment algorithms against the
      simulated ion lists and meaningful error rates can be computed. We anticipate that LC-MSsim will
      be useful to the wider community to perform benchmark studies and comparisons between
      computational tools.},
     author = {O. Schulz-Trieglaff and N. Pfeifer and C. Gr{\"o}pl and O. Kohlbacher and K. Reinert},
     journal = {BMC Bioinformatics},
     keywords = {algorithm, benchmark, lc-ms-ms, massspec, metabolomics, proteomics},
     number = {423},
     title = {LC-MSsim - a simulation software for liquid chromatography mass spectrometry data},
     url = {http://publications.imp.fu-berlin.de/408/},
     volume = {9},
     year = {2008}
    }
  • M. Sturm, B. Andreas, C. Gröpl, R. Hussong, E. Lange, N. Pfeifer, O. Schulz-Trieglaff, A. Zerck, K. Reinert, O. Kohlbacher, “OpenMS - An open-source software framework for mass spectrometry”, vol. 9, iss. 163, 2008.
    cite this publication
    @article{fu_mi_publications409,
     abstract = {BACKGROUND: Mass spectrometry is an essential analytical technique for high-throughput
      analysis in proteomics and metabolomics. The development of new separation techniques, precise
      mass analyzers and experimental protocols is a very active field of research. This leads to more
      complex experimental setups yielding ever increasing amounts of data. Consequently, analysis of
      the data is currently often the bottleneck for experimental studies. Although software tools for
      many data analysis tasks are available today, they are often hard to combine with each other or
      not flexible enough to allow for rapid prototyping of a new analysis workflow. RESULTS: We present
      OpenMS, a software framework for rapid application development in mass spectrometry. OpenMS has
      been designed to be portable, easy-to-use and robust while offering a rich functionality ranging
      from basic data structures to sophisticated algorithms for data analysis. This has already been
      demonstrated in several studies. CONCLUSIONS: OpenMS is available under the Lesser GNU Public
      License (LGPL) from the project website at http://www.openms.de.},
     author = {M. Sturm and B. Andreas and C. Gr{\"o}pl and R. Hussong and E. Lange and N. Pfeifer and
      O. Schulz-Trieglaff and A. Zerck and K. Reinert and O. Kohlbacher},
     journal = {BMC Bioinformatics},
     keywords = {lc-ms-ms, massspec, proteomics},
     number = {163},
     title = {OpenMS - An open-source software framework for mass spectrometry},
     url = {http://publications.imp.fu-berlin.de/409/},
     volume = {9},
     year = {2008}
    }
  • D. Weese, M. H. Schulz, P. Perner, “Efficient String Mining under Constraints via the Deferred Frequency Index”, 2008-07.
    cite this publication
    @inproceedings{fu_mi_publications412,
     abstract = {We propose a general approach for frequency based string mining, which has many
      applications, e.g. in contrast data mining. Our contribution is a novel algorithm based on a
      deferred data structure. Despite its simplicity, our approach is up to 4 times faster and uses
      about half the memory compared to the best-known algorithm of Fischer et al. Applications in
      various string domains, e.g. natural language, DNA or protein sequences, demonstrate the
      improvement of our algorithm.},
     author = {D. Weese and M. H. Schulz},
     booktitle = {Proceedings of the 8th Industrial Conference on Data Mining (ICDM'08)},
     editor = {P. Perner},
     month = {July},
     pages = {374--388},
     publisher = {Springer Verlag},
     title = {Efficient String Mining under Constraints via the Deferred Frequency Index},
     url = {http://publications.imp.fu-berlin.de/412/},
     year = {2008}
    }
  • A. Döring, D. Weese, T. Rausch, K. Reinert, “SeqAn -- An efficient, generic C++ library for sequence analysis”, vol. 9, iss. 1, 2008.
    cite this publication
    @article{fu_mi_publications455,
     abstract = {BACKGROUND:The use of novel algorithmic techniques is pivotal to many important
      problems in life science. For example the sequencing of the human genome [1] would not have been
      possible without advanced assembly algorithms. However, owing to the high speed of technological
      progress and the urgent need for bioinformatics tools, there is a widening gap between
      state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in
      widespread use.RESULTS:To remedy this trend we propose the use of SeqAn, a library of efficient
      data types and algorithms for sequence analysis in computational biology. SeqAn comprises
      implementations of existing, practical state-of-the-art algorithmic components to provide a sound
      basis for algorithm testing and development. In this paper we describe the design and content of
      SeqAn and demonstrate its use by giving two examples. In the first example we show an application
      of SeqAn as an experimental platform by comparing different exact string matching algorithms. The
      second example is a simple version of the well-known MUMmer tool rewritten in SeqAn. Results
      indicate that our implementation is very efficient and versatile to use.CONCLUSION:We anticipate
      that SeqAn greatly simplifies the rapid development of new bioinformatics tools by providing a
      collection of readily usable, well-designed algorithmic components which are fundamental for the
      field of sequence analysis. This leverages not only the implementation of new algorithms, but also
      enables a sound analysis and comparison of existing algorithms.},
     author = {A. D{\"o}ring and D. Weese and T. Rausch and K. Reinert},
     journal = {BMC Bioinformatics},
     number = {1},
     pages = {11},
     title = {SeqAn -- An efficient, generic C++ library for sequence analysis},
     url = {http://publications.imp.fu-berlin.de/455/},
     volume = {9},
     year = {2008}
    }

2007

  • E. Lange, C. Gröpl, O. Schulz-Trieglaff, A. Leinenbach, Ch. Huber, K. Reinert, “A Geometric Approach for the Alignment of Liquid Chromatography-Mass Spectrometry Data”, vol. 23, iss. 13, 2007.
    cite this publication
    @article{fu_mi_publications1133,
     abstract = {Motivation: Liquid chromatography coupled to mass spectrometry (LC-MS) and combined
      with tandem mass spectrometry (LC-MS/MS) have become a prominent tool for the analysis of complex
      proteomic samples. An important step in a typical workflow is the combination of results from
      multiple LC-MS experiments to improve confidence in the obtained measurements or to compare
      results from different samples. To do so, a suitable mapping or alignment between the data sets
      needs to be estimated. The alignment has to correct for variations in mass and elution time which
      are present in all mass spectrometry experiments. Results: We propose a novel algorithm to align
      LC-MS samples and to match corresponding ion species across samples. Our algorithm matches
      landmark signals between two data sets using a geometric technique based on pose clustering.
      Variations in mass and retention time are corrected by an affine dewarping function estimated from
      matched landmarks. We use the pairwise dewarping in an algorithm for aligning multiple samples. We
      show that our pose clustering approach is fast and reliable as compared to previous approaches. It
      is robust in the presence of noise and able to accurately align samples with only few common ion
      species. In addition, we can easily handle different kinds of LC-MS data and adopt our algorithm
      to new mass spectrometry technologies. Availability: This algorithm is implemented as part of the
      OpenMS software library for shotgun proteomics and available under the Lesser GNU Public License
      (LGPL) at www.openms.de},
     author = {E. Lange and C. Gr{\"o}pl and O. Schulz-Trieglaff and A. Leinenbach and Ch. Huber and K.
      Reinert},
     booktitle = {Proceedings of the 15th Annual International Conference on Intelligent Systems for
      Molecular Biology (ISMB) \&amp; 6th European Conference on Computational Biology (ECCB)},
     journal = {Oxford Journals},
     number = {13},
     pages = {i273--i281},
     publisher = {Oxford University Press},
     title = {A Geometric Approach for the Alignment of Liquid Chromatography-Mass Spectrometry Data},
     url = {http://publications.imp.fu-berlin.de/1133/},
     volume = {23},
     year = {2007}
    }
  • Witold Eryk Wolski, “Analysis of sets and collections of Peptide Mass Fingerprint data”, 2007-09-18.
    cite this publication
    @phdthesis{fu_mi_publications2536,
     abstract = {Recent advances in genomics, which outstanding achievements were exemplified by the
      complete sequencing of the human genome provided the infrastructure and information enabling the
      development of several proteomic technologies. Currently no single proteomic analysis strategy can
      sufficiently address the question of how the proteome is organised in terms of numerical
      complexity and complexity generated by the protein-protein interactions forming supramolecular
      complexes within the cell. In order to bring a detailed structural/functional picture of these
      complexes in whole genomes, cells, organelles or in normal and pathological states several
      proteomic strategies can be utilised. Combination of technologies will bring a more detailed
      answer to what are the components of certain cellular pathways (e.g.: targets of
      kinases/phosphatases, cytoskeletal proteins, signalling molecules), how do they interconnect, how
      are they modified in the cell and what are the roles of several complex components in normal and
      disease conditions. These types of studies depend on fast and high throughput methods of protein
      identification. One of the most common methods of analysis is mass spectrometric technique called
      peptide mapping. Peptide mapping is the comparison of mass spectrometrically determined peptide
      masses of a sequence specific digest of a single protein or peptide of interest with peptide
      masses predicted from genomic databases. In this work several contributions to the computational
      analysis of mass spectrometric data are presented. During the course of my studies I looked at the
      distribution of peptide masses in sequence specific protein sequence digests and developed a
      simple mathematical model dealing with peptide mass cluster centre location. I have introduced and
      studied the methods of calibration of mass spectrometric peak-list without resorting to internal
      or external calibration samples. Of importance is also contribution of this work to the
      calibration of data produced in high throughput experiments. In addition, I studied how filtering
      of non-peptide peaks influences the identification rates in mass spectrometric instruments.
      Furthermore, I focused my studies on measures of spectra similarity which can be used to acquire
      supplementary information, increasing the sensitivity and specificity of database searches.},
     author = {Witold Eryk Wolski},
     month = {September},
     school = {Freie Universit{\"a}t Berlin},
     title = {Analysis of sets and collections of Peptide Mass Fingerprint data},
     url = {http://publications.imp.fu-berlin.de/2536/},
     year = {2007}
    }
  • Wasinee Rungsarityotin, “Algorithm to identify protein complexes from high-throughput data”, 2007-12-03.
    cite this publication
    @phdthesis{fu_mi_publications2539,
     abstract = {Recent advances in proteomic technologies such as two-hybrid and biochemical
      purification allow large-scale investigations of protein interactions. The goal of this thesis is
      to investigate model-based approaches to predict protein complexes from tandem affinity
      purification experiments. We compare a simple overlapping model to a partitioning model. In
      addition, we propose a visualization framework to delineate overlapping complexes from
      experimental data. We propose two models to predict protein complexes from experimental data. Our
      first model is in some sense the simplest possible one. It is based on frequent itemset mining,
      which merely counts the incidence of certain sets of proteins within the experimental results. The
      affinity of two sets of proteins to form clusters is modeled to be independent, regardless of any
      overlapping members between these sets. Our second model assumes that formation of protein
      complexes can be reduced to pairwise interactions between proteins. Interactions between proteins
      are more likely for pairs of proteins if they come from the same cluster. Based on this model, we
      use Markov Random Field theory to calculate a maximum-likelihood assignment of proteins to
      clusters.},
     author = {Wasinee Rungsarityotin},
     month = {December},
     school = {Freie Universit{\"a}t Berlin},
     title = {Algorithm to identify protein complexes from high-throughput data},
     url = {http://publications.imp.fu-berlin.de/2539/},
     year = {2007}
    }
  • M. Bauer, G. W. Klau, K. Reinert, “Accurate multiple sequence-structure alignment of RNA sequences using combinatorial optimization.”, vol. 8, iss. 1, 2007-07.
    cite this publication
    @article{fu_mi_publications332,
     author = {M. Bauer and G. W. Klau and K. Reinert},
     journal = {BMC Bioinformatics},
     month = {July},
     number = {1},
     pages = {271},
     title = {Accurate multiple sequence-structure alignment of RNA sequences using combinatorial
      optimization.},
     url = {http://publications.imp.fu-berlin.de/332/},
     volume = {8},
     year = {2007}
    }
  • M. Bodirsky, C. Gröpl, D. Johannsen, M. Kang, “A direct decomposition of 3-connected planar graphs”, vol. B54Ak, 2007.
    cite this publication
    @article{fu_mi_publications336,
     address = {Taormina},
     author = {M. Bodirsky and C. Gr{\"o}pl and D. Johannsen and M. Kang},
     journal = {S{\'e}minaire Lotharingien de Combinatoire},
     keywords = {Three-Connected Planar Graph, Cnet, Planar Graph, Enumeration, Random graphs, Random
      Generation, Dynamic Programming, Graph Theory},
     pages = {15 pages},
     title = {A direct decomposition of 3-connected planar graphs},
     url = {http://publications.imp.fu-berlin.de/336/},
     volume = {B54Ak},
     year = {2007}
    }
  • M. Bodirsky, C. Gröpl, M. Kang, “Generating labeled planar graphs uniformly at random”, vol. 379, iss. 3, 2007.
    cite this publication
    @article{fu_mi_publications339,
     abstract = {We present a deterministic polynomial time algorithm to sample a labeled planar graph
      uniformly at random. Our approach uses recursive formulae for the exact number of labeled planar
      graphs with n vertices and m edges, based on a decomposition into 1-, 2-, and 3-connected
      components. We can then use known sampling algorithms and counting formulae for 3-connected planar
      graphs.},
     author = {M. Bodirsky and C. Gr{\"o}pl and M. Kang},
     journal = {Theoretical Computer Science},
     keywords = {Labeled planar graph, Enumeration, Decomposition, Sampling algorithm, Dynamic
      programming, Graph theory},
     number = {3},
     pages = {377--386},
     title = {Generating labeled planar graphs uniformly at random},
     url = {http://publications.imp.fu-berlin.de/339/},
     volume = {379},
     year = {2007}
    }
  • D. Fasulo, A.-K. Emde, L.-Y. Wang, N. J. Edwards, “Alignment of Mass Spectrometry Data by Clique Finding and Optimization”, vol. 4532, 2007.
    cite this publication
    @inproceedings{fu_mi_publications345,
     abstract = {Mass spectrometry (MS) is becoming a popular approach for quantifying the protein
      composition of complex samples. A great challenge for comparative proteomic profiling is to match
      corresponding peptide features from different experiments to ensure that the same protein
      intensities are correctly identified. Multi-dimensional data acquisition from
      liquid-chromatography mass spectrometry (LC-MS) makes the alignment problem harder. We propose a
      general paradigm for aligning peptide features using a bounded error model. Our method is tolerant
      of imperfect measurements, missing peaks, and extraneous peaks. It can handle an arbitrary number
      of dimensions of separation, and is very fast in practice even for large data sets. Finally, its
      parameters are intuitive and we describe a heuristic for estimating them automatically. We
      demonstrate results on single- and multi-dimensional data.},
     author = {D. Fasulo and A.-K. Emde and L.-Y. Wang and N. J. Edwards},
     booktitle = {Systems Biology and Computational Proteomics},
     pages = {119--129},
     publisher = {Springer Verlag},
     series = {Lecture Notes in Computer Science},
     title = {Alignment of Mass Spectrometry Data by Clique Finding and Optimization},
     url = {http://publications.imp.fu-berlin.de/345/},
     volume = {4532},
     year = {2007}
    }
  • G. W. Klau, S. Rahmann, A. Schliep, M. Vingron, K. Reinert, “Integer Linear Programming Approaches for Non-unique Probe Selection”, vol. 155, 2007.
    cite this publication
    @article{fu_mi_publications371,
     author = {G. W. Klau and S. Rahmann and A. Schliep and M. Vingron and K. Reinert},
     journal = {Discrete Applied Mathematics},
     pages = {840--856},
     title = {Integer Linear Programming Approaches for Non-unique Probe Selection},
     url = {http://publications.imp.fu-berlin.de/371/},
     volume = {155},
     year = {2007}
    }
  • P. May, G. W. Klau, M. Bauer, T. Steinke, “Accelerated microRNA Precursor Detection Using the Smith-Waterman Algorithm on FPGAs”, vol. 4360, 2007.
    cite this publication
    @inproceedings{fu_mi_publications384,
     author = {P. May and G. W. Klau and M. Bauer and T. Steinke},
     booktitle = {Proc. of GCCB 2006},
     pages = {19--32},
     series = {LNBI},
     title = {Accelerated microRNA Precursor Detection Using the Smith-Waterman Algorithm on FPGAs},
     url = {http://publications.imp.fu-berlin.de/384/},
     volume = {4360},
     year = {2007}
    }
  • Ch. Meier, “Bioinformatik: Aktuelle Proteinausstattung erlaubt Aussagen ĂŒber den Gesundheitszustand. Software hilft Ärzten kĂŒnftig bei der Diagnose.”, 2007-06.
    cite this publication
    @misc{fu_mi_publications386,
     author = {Ch. Meier},
     month = {June},
     note = {Der Artikel eines freien Medienjournalisten beschreibt den Einsatz von OpenMS in der
      Proteomik},
     title = {Bioinformatik: Aktuelle Proteinausstattung erlaubt Aussagen {\"u}ber den
      Gesundheitszustand. Software hilft {\"A}rzten k{\"u}nftig bei der Diagnose.},
     url = {http://publications.imp.fu-berlin.de/386/},
     year = {2007}
    }
  • K. Reinert, M. Bauer, A. Döring, A. L. Halpern, “A general paradigm for fast and adaptive clustering of biological sequences”, 2007.
    cite this publication
    @inproceedings{fu_mi_publications395,
     author = {K. Reinert and M. Bauer and A. D{\"o}ring and A. L. Halpern},
     booktitle = {German Conference on Bioinformatics (GCB 2007)},
     pages = {15--29},
     title = {A general paradigm for fast and adaptive clustering of biological sequences},
     url = {http://publications.imp.fu-berlin.de/395/},
     year = {2007}
    }
  • K. Reinert, D. H. Huson, “Sequence Assembly”, vol. 1, 2007-12.
    cite this publication
    @incollection{fu_mi_publications396,
     address = {Weinheim},
     author = {K. Reinert and D. H. Huson},
     month = {December},
     pages = {25--55},
     publisher = {Wiley-VCH},
     series = {Bioinformatics - From Genomes to Therapies},
     title = {Sequence Assembly},
     url = {http://publications.imp.fu-berlin.de/396/},
     volume = {1},
     year = {2007}
    }
  • O. Schulz-Trieglaff, R. Hussong, C. Gröpl, A. Hildebrandt, K. Reinert, “A Fast and Accurate Algorithm for the Quantification of Peptides from Mass Spectrometry data”, 2007.
    cite this publication
    @inproceedings{fu_mi_publications407,
     author = {O. Schulz-Trieglaff and R. Hussong and C. Gr{\"o}pl and A. Hildebrandt and K. Reinert},
     booktitle = {Proceedings of the Eleventh Annual International Conference on Research in
      Computational Molecular Biology (RECOMB 2007)},
     pages = {473--487},
     title = {A Fast and Accurate Algorithm for the Quantification of Peptides from Mass Spectrometry
      data},
     url = {http://publications.imp.fu-berlin.de/407/},
     year = {2007}
    }

2006

  • E. Althaus, A. Caprara, H.-P. Lenhof, K. Reinert, “A Branch-and-Cut Algorithm for Multiple Sequence Alignment”, iss. 105, 2006.
    cite this publication
    @article{fu_mi_publications325,
     author = {E. Althaus and A. Caprara and H.-P. Lenhof and K. Reinert},
     journal = {Mathematical Programming},
     number = {105},
     pages = {387--425},
     title = {A Branch-and-Cut Algorithm for Multiple Sequence Alignment},
     url = {http://publications.imp.fu-berlin.de/325/},
     year = {2006}
    }
  • O. Kohlbacher, K. Reinert, C. Gröpl, E. Lange, N. Pfeiffer, O. Schulz-Trieglaff, M. Sturm, “TOPP - The OpenMS Proteomics Pipeline”, 2006.
    cite this publication
    @inproceedings{fu_mi_publications375,
     abstract = {Motivation: Experimental techniques in proteomics have seen rapid development over the
      last few years. Volume and complexity of the data have both been growing at a similar rate.
      Accordingly, data management and analysis are one of the major challenges in proteomics. Flexible
      algorithms are required to handle changing experimental setups and to assist in developing and
      validating new methods. In order to facilitate these studies, it would be desirable to have a
      flexible `toolbox' of versatile and user-friendly applications allowing for rapid construction of
      computational workflows in proteomics. Results: We describe a set of tools for proteomics data
      analysis -- TOPP, The OpenMS Proteomics Pipeline. TOPP provides a set of computational tools which
      can be easily combined into analysis pipelines even by non-experts and can be used in proteomics
      workflows. These applications range from useful utilities (file format conversion, peak picking)
      over wrapper applications for known applications (e.g. Mascot) to completely new algorithmic
      techniques for data reduction and data analysis. We anticipate that TOPP will greatly facilitate
      rapid prototyping of proteomics data evaluation pipelines. As such, we describe the basic concepts
      and the current abilities of TOPP and illustrate these concepts in the context of two example
      applications: the identification of peptides from a raw data set through database search and the
      complex analysis of a standard addition experiment for the absolute quantitation of biomarkers.
      The latter example demonstrates TOPP's ability to construct flexible analysis pipelines in support
      of complex experimental setups. Availability: The TOPP components are available as open-source
      software under the lesser GNU public license (LGPL). Source code is available from the project web
      site at www.OpenMS.de},
     author = {O. Kohlbacher and K. Reinert and C. Gr{\"o}pl and E. Lange and N. Pfeiffer and O.
      Schulz-Trieglaff and M. Sturm},
     booktitle = {Proceedings of the 5th European Conference on Computational Biology (ECCB 2006)},
     title = {TOPP - The OpenMS Proteomics Pipeline},
     url = {http://publications.imp.fu-berlin.de/375/},
     year = {2006}
    }
  • E. Lange, C. Gröpl, K. Reinert, A. Hildebrandt, “High Accuracy Peak-Picking of Proteomics Data using Wavelet Techniques”, 2006.
    cite this publication
    @inproceedings{fu_mi_publications376,
     author = {E. Lange and C. Gr{\"o}pl and K. Reinert and A. Hildebrandt},
     booktitle = {Proceedings of the 11th Pacific Symposium on Biocomputing (PSB-06)},
     pages = {243--254},
     title = {High Accuracy Peak-Picking of Proteomics Data using Wavelet Techniques},
     url = {http://publications.imp.fu-berlin.de/376/},
     year = {2006}
    }
  • B. M. Mayr, O. Kohlbacher, K. Reinert, C. Gröpl, E. Lange, C. L. Klein, Ch. Huber, “Absolute Myoglobin Quantitation in Serum by Combining Two-Dimensional Liquid Chromatography-Electrospray Ionization Mass Spectrometry and Novel Data Analysis Algorithms”, vol. 5, 2006.
    cite this publication
    @article{fu_mi_publications385,
     author = {B. M. Mayr and O. Kohlbacher and K. Reinert and C. Gr{\"o}pl and E. Lange and C. L. Klein
      and Ch. Huber},
     journal = {Journal of Proteome Research},
     pages = {414--421},
     title = {Absolute Myoglobin Quantitation in Serum by Combining Two-Dimensional Liquid
      Chromatography-Electrospray Ionization Mass Spectrometry and Novel Data Analysis Algorithms},
     url = {http://publications.imp.fu-berlin.de/385/},
     volume = {5},
     year = {2006}
    }
  • T. Rausch, “Discovering causes of multifactorial diseases”, 2006-09.
    cite this publication
    @unpublished{fu_mi_publications389,
     author = {T. Rausch},
     month = {September},
     school = {Hasso-Plattner-Institut f{\"u}r Softwaresystemtechnik GmbH, Universit{\"a}t Potsdam},
     title = {Discovering causes of multifactorial diseases},
     url = {http://publications.imp.fu-berlin.de/389/},
     year = {2006}
    }
  • K. Reinert, O. Kohlbacher, C. Gröpl, E. Lange, O. Schulz-Trieglaff, M. Sturm, N. Pfeifer, C. G. Huber, O. Kohlbacher, K. Reinert, “OpenMS - A Framework for Quantitative HPLC/MS-Based Proteomics”, iss. 5471, 2006.
    cite this publication
    @inproceedings{fu_mi_publications397,
     author = {K. Reinert and O. Kohlbacher and C. Gr{\"o}pl and E. Lange and O. Schulz-Trieglaff and M.
      Sturm and N. Pfeifer},
     booktitle = {Computational Proteomics},
     editor = {C. G. Huber and O. Kohlbacher and K. Reinert},
     note = {{\ensuremath{<}}span
      class='mathrm'{\ensuremath{>}}\&lt;{\ensuremath{<}}/span{\ensuremath{>}}http://drops.dagstuhl.de/opus/volltexte/2006/546{\ensuremath{<}}span
      class='mathrm'{\ensuremath{>}}\&gt;{\ensuremath{<}}/span{\ensuremath{>}} [date of citation:
      2006-01-01]},
     number = {05471},
     publisher = {Internationales Begegnungs- und Forschungszentrum f{\~A}?r Informatik (IBFI), Schloss
      Dagstuhl, Germany},
     series = {Dagstuhl Seminar Proceedings},
     title = {OpenMS - A Framework for Quantitative HPLC/MS-Based Proteomics},
     url = {http://publications.imp.fu-berlin.de/397/},
     year = {2006}
    }
  • W. E. Wolski, M. Farrow, A.-K. Emde, L. Maciej, H. Lehrach, K. Reinert, “Analytical model of peptide mass cluster centres with applications”, vol. 4, iss. 18, 2006.
    cite this publication
    @article{fu_mi_publications415,
     author = {W. E. Wolski and M. Farrow and A.-K. Emde and L. Maciej and H. Lehrach and K. Reinert},
     journal = {Proteome Science},
     number = {18},
     pages = {doi:10.1186/1477--5956},
     title = {Analytical model of peptide mass cluster centres with applications},
     url = {http://publications.imp.fu-berlin.de/415/},
     volume = {4},
     year = {2006}
    }
  • D. Weese, “Entwurf und Implementierung eines generischen Substring-Index”, p. 99, 2006-05-02.
    cite this publication
    @phdthesis{fu_mi_publications457,
     author = {D. Weese},
     month = {May},
     school = {Humboldt-University},
     title = {Entwurf und Implementierung eines generischen Substring-Index},
     url = {http://publications.imp.fu-berlin.de/457/},
     year = {2006}
    }

2005

  • V. Bafna, K. Reinert, “Mass Spectrometry and Computational Proteomics”, 2005.
    cite this publication
    @incollection{fu_mi_publications327,
     author = {V. Bafna and K. Reinert},
     booktitle = {Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics},
     publisher = {Wiley-Eastern},
     title = {Mass Spectrometry and Computational Proteomics},
     url = {http://publications.imp.fu-berlin.de/327/},
     year = {2005}
    }
  • M. Bauer, G. W. Klau, K. Reinert, “Multiple Structural RNA Alignment with Lagrangian Relaxation”, 2005.
    cite this publication
    @inproceedings{fu_mi_publications333,
     author = {M. Bauer and G. W. Klau and K. Reinert},
     booktitle = {Proceedings of the 5th Workshop on Algorithms Bioinformatics (WABI-05)},
     pages = {303--314},
     title = {Multiple Structural RNA Alignment with Lagrangian Relaxation},
     url = {http://publications.imp.fu-berlin.de/333/},
     year = {2005}
    }
  • M. Bauer, G. W. Klau, K. Reinert, “Fast and Accurate Structural RNA Alignment by Progressive Lagrangian Relaxation”, 2005.
    cite this publication
    @inproceedings{fu_mi_publications334,
     author = {M. Bauer and G. W. Klau and K. Reinert},
     booktitle = {Proceedings of the 1st International Symposium on Computational Life Science
      (CompLife-05)},
     pages = {217--228},
     title = {Fast and Accurate Structural RNA Alignment by Progressive Lagrangian Relaxation},
     url = {http://publications.imp.fu-berlin.de/334/},
     year = {2005}
    }
  • M. Bodirsky, C. Gröpl, D. Johannsen, M. Kang, “A direct decomposition of 3-connected planar graphs”, 2005.
    cite this publication
    @inproceedings{fu_mi_publications337,
     address = {Taormina},
     author = {M. Bodirsky and C. Gr{\"o}pl and D. Johannsen and M. Kang},
     booktitle = {Proceedings of the 17th Annual International Conference on Formal Power Series and
      Algebraic Combinatorics (FPSAC05)},
     keywords = {Three-Connected Planar Graph, Cnet, Planar Graph, Enumeration, Random graphs, Random
      Generation, Dynamic Programming, Graph Theory},
     title = {A direct decomposition of 3-connected planar graphs},
     url = {http://publications.imp.fu-berlin.de/337/},
     year = {2005}
    }
  • M. Bodirsky, C. Gröpl, M. Kang, “Sampling Unlabeled Biconnected Planar Graphs”, 2005.
    cite this publication
    @inproceedings{fu_mi_publications340,
     author = {M. Bodirsky and C. Gr{\"o}pl and M. Kang},
     booktitle = {Proceedings of the 16th Annual International Symposium on Algorithms and Computation
      (ISAAC05)},
     keywords = {Planar Graph, Enumeration, Random graphs, Random Generation, Graph Theory},
     title = {Sampling Unlabeled Biconnected Planar Graphs},
     url = {http://publications.imp.fu-berlin.de/340/},
     year = {2005}
    }
  • C. Gröpl, “An Algorithm for Feature Finding in LC/MS Raw Data”, 2005.
    cite this publication
    @inproceedings{fu_mi_publications347,
     author = {C. Gr{\"o}pl},
     booktitle = {Computational Proteomics},
     note = {Extended abstract for talk given at Dagstuhl Seminar 05471 on Computational Proteomics,
      20.-25. November 2005},
     publisher = {Dagstuhl Online Publication Server (DROPS)},
     title = {An Algorithm for Feature Finding in LC/MS Raw Data},
     url = {http://publications.imp.fu-berlin.de/347/},
     year = {2005}
    }
  • C. Gröpl, A. Hildebrandt, E. Lange, S. Lövenich, M. Sturm, “OpenMS - Software for Mass Spectrometry”, 2005.
    cite this publication
    @misc{fu_mi_publications351,
     author = {C. Gr{\"o}pl and A. Hildebrandt and E. Lange and S. L{\"o}venich and M. Sturm},
     keywords = {mass spectrometry, proteomics, open source software},
     note = {http://mbi.osu.edu/2004/workshops2004.html},
     title = {OpenMS - Software for Mass Spectrometry},
     url = {http://publications.imp.fu-berlin.de/351/},
     year = {2005}
    }
  • C. Gröpl, A. Hildebrandt, E. Lange, M. Sturm, “OpenMS - a generic open source framework for HPLC/MS-based proteomics”, 2005.
    cite this publication
    @misc{fu_mi_publications352,
     author = {C. Gr{\"o}pl and A. Hildebrandt and E. Lange and M. Sturm},
     keywords = {mass spectrometry, proteomics, open source software},
     note = {http://www.hupo2005.com/},
     title = {OpenMS - a generic open source framework for HPLC/MS-based proteomics},
     url = {http://publications.imp.fu-berlin.de/352/},
     year = {2005}
    }
  • C. Gröpl, E. Lange, K. Reinert, M. Sturm, Ch. Huber, B. M. Mayr, C. L. Klein, “Algorithms for the automated absolute quantification of diagnostic markers in complex proteomics samples”, 2005.
    cite this publication
    @inproceedings{fu_mi_publications358,
     abstract = {HPLC-ESI-MS is rapidly becoming an established standard method for shotgun proteomics.
      Currently, its major drawbacks are twofold: quantification is mostly limited to relative
      quantification and the large amount of data produced by every individual experiment can make
      manual analysis quite difficult. Here we present a new, combined experimental and algorithmic
      approach to absolutely quantify proteins from samples with unprecedented precision. We apply the
      method to the analysis of myoglobin in human blood serum, which is an important diagnostic marker
      for myocardial infarction. Our approach was able to determine the absolute amount of myoglobin in
      a serum sample through a series of standard addition experiments with a relative error of 2.5
      percent. Compared to a manual analysis of the same dataset we could improve the precision and
      conduct it in a fraction of the time needed for the manual analysis. We anticipate that our
      automatic quantitation method will facilitate further absolute or relative quantitation of even
      more complex peptide samples. The algorithm was developed using our publically available software
      framework OpenMS (www.openms.de).},
     author = {C. Gr{\"o}pl and E. Lange and K. Reinert and M. Sturm and Ch. Huber and B. M. Mayr and C.
      L. Klein},
     booktitle = {Proceedings of the 1st International Symposium on Computational Life Science
      (CompLife05)},
     pages = {151--163},
     title = {Algorithms for the automated absolute quantification of diagnostic markers in complex
      proteomics samples},
     url = {http://publications.imp.fu-berlin.de/358/},
     year = {2005}
    }
  • C. L. Klein, O. Kohlbacher, K. Reinert, “Reference methods and materials in standardisation and quality assurance (abstract)”, vol. 272, iss. Supplement 1, 2005.
    cite this publication
    @article{fu_mi_publications373,
     author = {C. L. Klein and O. Kohlbacher and K. Reinert},
     journal = {FEBS Journal},
     number = {Supplement 1},
     pages = {490--504},
     title = {Reference methods and materials in standardisation and quality assurance (abstract)},
     url = {http://publications.imp.fu-berlin.de/373/},
     volume = {272},
     year = {2005}
    }
  • E. Lange, C. Gröpl, K. Reinert, A. Hildebrandt, “High-accuracy peak picking of proteomics data”, 2005.
    cite this publication
    @inproceedings{fu_mi_publications377,
     author = {E. Lange and C. Gr{\"o}pl and K. Reinert and A. Hildebrandt},
     booktitle = {Computational Proteomics},
     note = {Extended abstract for talk given at Dagstuhl Seminar 05471 on Computational Proteomics,
      20.-25. November 2005},
     publisher = {Dagstuhl Online Publication Server (DROPS)},
     title = {High-accuracy peak picking of proteomics data},
     url = {http://publications.imp.fu-berlin.de/377/},
     year = {2005}
    }
  • K. Reinert, O. Kohlbacher, C. Gröpl, E. Lange, O. Schulz-Trieglaff, M. Sturm, N. Pfeifer, “OpenMS - A Framework for Quantitative HPLC/MS-Based Proteomics”, 2005.
    cite this publication
    @inproceedings{fu_mi_publications398,
     author = {K. Reinert and O. Kohlbacher and C. Gr{\"o}pl and E. Lange and O. Schulz-Trieglaff and M.
      Sturm and N. Pfeifer},
     booktitle = {Computational Proteomics},
     note = {Extended abstract for talk given at Dagstuhl Seminar 05471 on Computational Proteomics,
      20.-25. November 2005},
     publisher = {Dagstuhl Online Publication Server (DROPS)},
     title = {OpenMS - A Framework for Quantitative HPLC/MS-Based Proteomics},
     url = {http://publications.imp.fu-berlin.de/398/},
     year = {2005}
    }
  • O. Schulz-Trieglaff, “Modelling the Randomness in Biological Systems”, 2005.
    cite this publication
    @misc{fu_mi_publications402,
     author = {O. Schulz-Trieglaff},
     keywords = {petri nets, Gillespie algorithm},
     title = {Modelling the Randomness in Biological Systems},
     url = {http://publications.imp.fu-berlin.de/402/},
     year = {2005}
    }
  • O. Schulz-Trieglaff, “Software Platforms for Computational Proteomics”, 2005.
    cite this publication
    @inproceedings{fu_mi_publications403,
     author = {O. Schulz-Trieglaff},
     booktitle = {Computational Proteomics},
     note = {Extended abstract for talk given at Dagstuhl Seminar 05471 on Computational Proteomics,
      20.-25. November 2005},
     publisher = {Dagstuhl Online Publication Server (DROPS)},
     title = {Software Platforms for Computational Proteomics},
     url = {http://publications.imp.fu-berlin.de/403/},
     year = {2005}
    }
  • W. E. Wolski, M. Lalowski, P. Jungblut, K. Reinert, “Calibration of mass spectrometric peptide mass fingerprint data without specific external or internal calibrants”, vol. 6, iss. 203, 2005.
    cite this publication
    @article{fu_mi_publications413,
     author = {W. E. Wolski and M. Lalowski and P. Jungblut and K. Reinert},
     journal = {BMC Bioinformatics},
     number = {203},
     pages = {http://www.biomedcentral.com/1471--2105/6/203},
     title = {Calibration of mass spectrometric peptide mass fingerprint data without specific external
      or internal calibrants},
     url = {http://publications.imp.fu-berlin.de/413/},
     volume = {6},
     year = {2005}
    }
  • E. Wolski, M. Lalowski, P. Martus, P. Giavalisco, J. Gobom, A. Sickmann, H. Lehrach, K. Reinert, “Transformation and other factors of the peptide mass spectormetry pairwise peaklist comparison process”, vol. 6, iss. 285, 2005.
    cite this publication
    @article{fu_mi_publications414,
     author = {E. Wolski and M. Lalowski and P. Martus and P. Giavalisco and J. Gobom and A. Sickmann
      and H. Lehrach and K. Reinert},
     journal = {BMC Bioinformatics},
     number = {285},
     pages = {http://www.biomedcentral.com/1471--2105/6/285},
     title = {Transformation and other factors of the peptide mass spectormetry pairwise peaklist
      comparison process},
     url = {http://publications.imp.fu-berlin.de/414/},
     volume = {6},
     year = {2005}
    }

2004

  • M. Bauer, G. W. Klau, “Structural Alignment of Two RNA Sequences with Lagrangian Relaxation”, 2004.
    cite this publication
    @inproceedings{fu_mi_publications330,
     author = {M. Bauer and G. W. Klau},
     booktitle = {Proceedings of the 15th International Symposium, ISAAC 2004, Hong Kong},
     pages = {113--125},
     publisher = {Springer Verlag},
     series = {LNCS 3341},
     title = {Structural Alignment of Two RNA Sequences with Lagrangian Relaxation},
     url = {http://publications.imp.fu-berlin.de/330/},
     year = {2004}
    }
  • E. Lange, “Peak picking in mass spectra”, 2004.
    cite this publication
    @misc{fu_mi_publications344,
     abstract = {High throughput analysis of proteins using mass spectrometry requires an efficient
      signal preprocessing which reduces the amount of data with minimal loss of information. Therefore
      the peaks that belong to a peptide have to be detected, and important features like their peak
      centroid position, the height and the area have to be determined. Here we present a peak picking
      algorithm which detects peaks in a noisy mass spectrum using its continuous wavelet transform. By
      adapting the wavelet to the theoretical peak shape, each peaks centroid position is precisely
      identified; thus, overlapping peaks (e.g. caused by electronspray ionization) are well separated.
      Representing each peak not only by its centroid position and area but also by the parameters of
      the best fitting asymmetric lorentzian or hyperbolic secant squared functions, yields valuable
      information about the original peak shape for further analysis. Given a mass spectrum with 100,000
      raw data points representing 200 peaks, our algorithm stored 5 parameters per peak, and was able
      to reduce the memory requirement down to 1 percent.},
     author = {E. Lange},
     title = {Peak picking in mass spectra},
     url = {http://publications.imp.fu-berlin.de/344/},
     year = {2004}
    }
  • C. Gröpl, H.-J. Prömel, A. Srivastav, “Ordered binary decision diagrams and the Shannon effect”, vol. 142, 2004.
    cite this publication
    @article{fu_mi_publications360,
     abstract = {We investigate the size and structure of ordered binary decision diagrams (OBDDs) for
      random Boolean functions. It was known that for most values of n, the expected OBDD size of a
      random Boolean function with n variables is equal to the worst-case size up to terms of lower
      order. Such a phenomenon is generally called strong Shannon effect. Here we show that the strong
      Shannon effect is not valid for all n. Instead it undergoes a certain periodic `phase transition':
      If n lies within intervals of constant width around the values n = 2h + h, then the strong Shannon
      effect does not hold, whereas it does hold outside these intervals. Our analysis provides doubly
      exponential probability bounds and generalises to ordered Kronecker functional decision diagrams
      (OKFDDs).},
     author = {C. Gr{\"o}pl and H.-J. Pr{\"o}mel and A. Srivastav},
     journal = {Discrete Applied Mathematics},
     keywords = {VLSI-Design and layout, Binary Decision Diagrams, Graph theory (other), Hardware
      verification, Probability theory, Random graphs, Randomized algorithms and probabilistic analysis,
      Theoretical computer science (other)},
     pages = {67--85},
     title = {Ordered binary decision diagrams and the Shannon effect},
     url = {http://publications.imp.fu-berlin.de/360/},
     volume = {142},
     year = {2004}
    }
  • S. Istrail, G. G. Sutton, L. Florea, C. M. Mobarry, R. Lippert, B. Walenz, H. Shatkay, Ian Dew, J. R. Miller, M. J. Flanigan, N. J. Edwards, R. Bolanos, D. Fasulo, B. V. Halldorsson, S. Hannenhalli, R. J. Turner, S. Yooseph, Fu Lu, D. R. Nusskern, B. C. Shue, X. H. Zheng, F. Zhong, A. L. Delcher, D. H. Huson, S. A. Kravitz, L. Mouchard, K. Reinert, K. A. Remington, A. G. Clark, M. S. Waterman, E. E. Eichler, M. D. Adams, M. W. Hunkapillar, E. W. Myers, J. C. Venter, “Whole-genome shotgun assembly and comparison of human genome assemblies”, vol. 101, iss. 7, 2004.
    cite this publication
    @article{fu_mi_publications369,
     author = {S. Istrail and G. G. Sutton and L. Florea and C. M. Mobarry and R. Lippert and B. Walenz
      and H. Shatkay and Ian Dew and J. R. Miller and M. J. Flanigan and N. J. Edwards and R. Bolanos
      and D. Fasulo and B. V. Halldorsson and S. Hannenhalli and R. J. Turner and S. Yooseph and Fu Lu
      and D. R. Nusskern and B. C. Shue and X. H. Zheng and F. Zhong and A. L. Delcher and D. H. Huson
      and S. A. Kravitz and L. Mouchard and K. Reinert and K. A. Remington and A. G. Clark and M. S.
      Waterman and E. E. Eichler and M. D. Adams and M. W. Hunkapillar and E. W. Myers and J. C.
      Venter},
     journal = {Proceedings of the national academy of science (PNAS)},
     number = {7},
     pages = {1916--1921},
     title = {Whole-genome shotgun assembly and comparison of human genome assemblies},
     url = {http://publications.imp.fu-berlin.de/369/},
     volume = {101},
     year = {2004}
    }
  • G. W. Klau, S. Rahmann, A. Schliep, K. Reinert, “Optimal Robust Non-Unique Probe Selection Using Integer Linear Programming”, 2004.
    cite this publication
    @inproceedings{fu_mi_publications372,
     author = {G. W. Klau and S. Rahmann and A. Schliep and K. Reinert},
     booktitle = {Proceedings of the Twelfth International Conference on Intelligent Systems for
      Molecular Biology (ISMB-04)},
     pages = {186--193},
     title = {Optimal Robust Non-Unique Probe Selection Using Integer Linear Programming},
     url = {http://publications.imp.fu-berlin.de/372/},
     year = {2004}
    }
  • O. Kohlbacher, K. Reinert, “Differenzielle Proteomanalyse -- Experimentelle Methoden, Algorithmische Herausforderungen”, vol. 46, 2004.
    cite this publication
    @article{fu_mi_publications374,
     author = {O. Kohlbacher and K. Reinert},
     journal = {it -- Information technology},
     pages = {31--38},
     title = {Differenzielle Proteomanalyse -- Experimentelle Methoden, Algorithmische
      Herausforderungen},
     url = {http://publications.imp.fu-berlin.de/374/},
     volume = {46},
     year = {2004}
    }

2003

  • M. Bodirsky, C. Gröpl, M. Kang, “Generating labeled planar graphs uniformly at random”, iss. 2719, 2003.
    cite this publication
    @inproceedings{fu_mi_publications341,
     abstract = {We present an expected polynomial time algorithm to generate a labeled planar graph
      uniformly at random. To generate the planar graphs, we derive recurrence formulas that count all
      such graphs with n vertices and m edges, based on a decomposition into 1-, 2-, and 3-connected
      components. For 3-connected graphs we apply a recent random generation algorithm by Schaeffer and
      a counting formula by Mullin and Schellenberg.},
     author = {M. Bodirsky and C. Gr{\"o}pl and M. Kang},
     booktitle = {Proceedings of ICALP 2003},
     keywords = {Planar Graph, Enumeration, Random graphs, Random Generation, Dynamic Programming, Graph
      Theory},
     note = {Appeared 2008 in Theoretical Computer Science. \{ The download is the journal submission
      \&lt;br\&gt; From time to time we receive requests for source code, so here it is: See the files
      BGK03b.README and GBK03b.tar.bz2 \}},
     number = {2719},
     pages = {1095--1107},
     publisher = {Springer Verlag},
     series = {Lecture Notes in Computer Science},
     title = {Generating labeled planar graphs uniformly at random},
     url = {http://publications.imp.fu-berlin.de/341/},
     year = {2003}
    }
  • M. Bodirsky, C. Gröpl, M. Kang, “Decomposing, Counting, and Generating Unlabeled Cubic Planar Graphs”, 2003.
    cite this publication
    @inproceedings{fu_mi_publications342,
     abstract = {We present an expected polynomial time algorithm to generate an unlabeled connected
      cubic planar graph uniformly at random. We first consider rooted cubic planar graphs, i.e., we
      count connected cubic planar graphs up to isomorphisms that fix a certain directed edge. Based on
      decompositions along the connectivity structure, we derive recurrence formulas for counting the
      exact number of rooted cubic planar graphs. This leads to 3-connected planar graphs, which have a
      unique embedding on the sphere; but special care has to be taken for rooted graphs that have a
      sense-reversing automorphism. Therefore we introduce the concept of colored networks, which stand
      in bijective correspondence to rooted graphs with given symmetries. Colored networks can again be
      decomposed along their connectivity structure. For rooted 3-connected cubic planar graphs embedded
      in the plane, we switch to the dual and count rooted triangulations. All these numbers can be
      evaluated in polynomial time by dynamic programming. We can use them to generate rooted cubic
      planar graphs uniformly at random. To generate connected cubic planar graphs without a root
      uniformly at random, we apply rejection sampling and obtain an expected polynomial time
      algorithm.},
     author = {M. Bodirsky and C. Gr{\"o}pl and M. Kang},
     booktitle = {European Conference on Combinatorics, Graph Theory, and Applications EUROCOMB'03
      Prague},
     keywords = {Cubic Planar Graph, Planar Graph, Cubic Graph, Enumeration, Random graphs, Random
      Generation, Dynamic Programming, Graph Theory},
     title = {Decomposing, Counting, and Generating Unlabeled Cubic Planar Graphs},
     url = {http://publications.imp.fu-berlin.de/342/},
     year = {2003}
    }
  • C. Frömmel, Ch. Gille, A. Goede, C. Gröpl, S. Hougardy, T. Nierhoff, R. Preissner, M. Thimm, “Accelerating screening of 3D protein data with a graph theoretical approach”, vol. 19, iss. 18, 2003-12.
    cite this publication
    @article{fu_mi_publications346,
     abstract = {Motivation: The Dictionary of Interfaces in Proteins (DIP) is a database collecting the
      3D structure of interacting parts of proteins that are called patches. It serves as a repository,
      in which patches similar to given query patches can be found. The computation of the similarity of
      two patches is time consuming and traversing the entire DIP requires some hours. In this work we
      address the question of how the patches similar to a given query can be identified by scanning
      only a small part of DIP. The answer to this question requires the investigation of the
      distribution of the similarity of patches. Results: The score values describing the similarity of
      two patches can roughly be divided into three ranges that correspond to different levels of
      spatial similarity. Interestingly, the two iso-score lines separating the three classes can be
      determined by two different approaches. Applying a concept of the theory of random graphs reveals
      significant structural properties of the data in DIP. These can be used to accelerate scanning the
      DIP for patches similar to a given query. Searches for very similar patches could be accelerated
      by a factor of more than 25. Patches with a medium similarity could be found 10 times faster than
      by brute-force search. 10.1093/bioinformatics/btg343},
     author = {C. Fr{\"o}mmel and Ch. Gille and A. Goede and C. Gr{\"o}pl and S. Hougardy and T.
      Nierhoff and R. Preissner and M. Thimm},
     journal = {Bioinformatics},
     keywords = {algorithm, proteomics, statistics},
     month = {December},
     number = {18},
     pages = {2442--2447},
     title = {Accelerating screening of 3D protein data with a graph theoretical approach},
     url = {http://publications.imp.fu-berlin.de/346/},
     volume = {19},
     year = {2003}
    }
  • C. Gröpl, “Algorithmen in der Bioinformatik”, 2003.
    cite this publication
    @misc{fu_mi_publications348,
     author = {C. Gr{\"o}pl},
     note = {Skript zu meiner Vorlesung im Wintersemester 2002/03 am Institut f{\"u}r Informatik der
      Humboldt-Universit{\"a}t zu Berlin},
     title = {Algorithmen in der Bioinformatik},
     url = {http://publications.imp.fu-berlin.de/348/},
     year = {2003}
    }

2002

  • E. Althaus, A. Caprara, H.-P. Lenhof, K. Reinert, “Multiple Sequence alignment with arbitrary gap costs: Computing an optimal solution using polyhedral combinatorics”, 2002.
    cite this publication
    @inproceedings{fu_mi_publications326,
     author = {E. Althaus and A. Caprara and H.-P. Lenhof and K. Reinert},
     booktitle = {Proceedings of the 1st European Conference on Computational Biology (ECCB 2002)},
     pages = {4--16},
     title = {Multiple Sequence alignment with arbitrary gap costs: Computing an optimal solution using
      polyhedral combinatorics},
     url = {http://publications.imp.fu-berlin.de/326/},
     year = {2002}
    }
  • J. A. Bailey, Z. Gu, R. A. Clark, K. Reinert, R. V. Samonte, S. S. Schwartz, M. D. Adams, E. W. Myers, P. Li, E. E. Eichler, “Recent Segmental Duplications in the Human Genome”, vol. 297, 2002.
    cite this publication
    @article{fu_mi_publications328,
     author = {J. A. Bailey and Z. Gu and R. A. Clark and K. Reinert and R. V. Samonte and S. S.
      Schwartz and M. D. Adams and E. W. Myers and P. Li and E. E. Eichler},
     journal = {Science},
     pages = {1003--1007},
     title = {Recent Segmental Duplications in the Human Genome},
     url = {http://publications.imp.fu-berlin.de/328/},
     volume = {297},
     year = {2002}
    }
  • C. Gröpl, S. Hougardy, T. Nierhoff, H.-J. Prömel, “Steiner trees in uniformly quasi-bipartite graphs”, vol. 83, 2002.
    cite this publication
    @article{fu_mi_publications354,
     abstract = {The area of approximation algorithms for the Steiner tree problem in graphs has seen
      continuous progress over the last years. Currently the best approximation algorithm has a
      performance ratio of 1.550. This is still far away from 1.0074, the largest known lower bound on
      the achievable performance ratio. As all instances resulting from known lower bound reductions are
      uniformly quasi-bipartite, it is interesting whether this special case can be approximated better
      than the general case. We present an approximation algorithm with performance ratio 73/60 \&lt;
      1.217 for the uniformly quasi-bipartite case. This improves on the previously known ratio of 1.279
      of Robins and Zelikovsky. We use a new method of analysis that combines ideas from the greedy
      algorithm for set cover with a matroid-style exchange argument to model the connectivity
      constraint. As a consequence, we are able to provide a tight instance.},
     author = {C. Gr{\"o}pl and S. Hougardy and T. Nierhoff and H.-J. Pr{\"o}mel},
     journal = {Information Processing Letters},
     keywords = {Steiner trees, Graph algorithms, Approximation algorithms},
     pages = {195--200},
     title = {Steiner trees in uniformly quasi-bipartite graphs},
     url = {http://publications.imp.fu-berlin.de/354/},
     volume = {83},
     year = {2002}
    }
  • C. Gröpl, S. Hougardy, T. Nierhoff, H.-J. Prömel, M. Thimm, “Approximationsalgorithmen fĂŒr das Steinerbaumproblem in Graphen”, 2002.
    cite this publication
    @misc{fu_mi_publications356,
     author = {C. Gr{\"o}pl and S. Hougardy and T. Nierhoff and H.-J. Pr{\"o}mel and M. Thimm},
     title = {Approximationsalgorithmen f{\"u}r das Steinerbaumproblem in Graphen},
     url = {http://publications.imp.fu-berlin.de/356/},
     year = {2002}
    }
  • A. L. Halpern, D. H. Huson, K. Reinert, “Segment Match refinment and applications”, 2002.
    cite this publication
    @inproceedings{fu_mi_publications364,
     author = {A. L. Halpern and D. H. Huson and K. Reinert},
     booktitle = {Proceedings of the 2nd Workshop on Algorithms Bioinformatics (WABI-02)},
     pages = {126--139},
     title = {Segment Match refinment and applications},
     url = {http://publications.imp.fu-berlin.de/364/},
     year = {2002}
    }
  • D. H. Huson, K. Reinert, E. W. Myers, “The Greedy Path-Merging Algorithm for Sequence Assembly”, vol. 49, iss. 5, 2002.
    cite this publication
    @article{fu_mi_publications367,
     author = {D. H. Huson and K. Reinert and E. W. Myers},
     journal = {Journal of the ACM},
     number = {5},
     pages = {603--615},
     title = {The Greedy Path-Merging Algorithm for Sequence Assembly},
     url = {http://publications.imp.fu-berlin.de/367/},
     volume = {49},
     year = {2002}
    }
  • Richard Mural, M. D. Adams, K. Reinert, “A Comparison of Whole-Genome Shotgun-Derived Mouse Chromosome 16 and the Human Genome”, vol. 296, 2002.
    cite this publication
    @article{fu_mi_publications387,
     abstract = {The high degree of similarity between the mouse and human genomes is demonstrated
      through analysis of the sequence of mouse chromosome 16 (Mmu 16), which was obtained as part of a
      whole-genome shotgun assembly of the mouse genome. The mouse genome is about 10\% smaller than the
      human genome, owing to a lower repetitive DNA content. Comparison of the structure and
      protein-coding potential of Mmu 16 with that of the homologous segments of the human genome
      identifies regions of conserved synteny with human chromosomes (Hsa) 3, 8, 12, 16, 21, and 22.
      Gene content and order are highly conserved between Mmu 16 and the syntenic blocks of the human
      genome. Of the 731 predicted genes on Mmu 16, 509 align with orthologs on the corre- sponding
      portions of the human genome, 44 are likely paralogous to these genes, and 164 genes have homologs
      elsewhere in the human genome; there are 14 genes for which we could find no human counterpart.},
     author = {Richard Mural and M. D. Adams and K. Reinert},
     journal = {Science},
     pages = {1661--1671},
     title = {A Comparison of Whole-Genome Shotgun-Derived Mouse Chromosome 16 and the Human Genome},
     url = {http://publications.imp.fu-berlin.de/387/},
     volume = {296},
     year = {2002}
    }

2001

  • C. Gröpl, S. Hougardy, T. Nierhoff, H.-J. Prömel, X. Cheng, D. Z. Du, “Approximation Algorithms for the Steiner Tree Problem in Graphs”, 2001.
    cite this publication
    @incollection{fu_mi_publications353,
     author = {C. Gr{\"o}pl and S. Hougardy and T. Nierhoff and H.-J. Pr{\"o}mel},
     booktitle = {Steiner Trees in Industry},
     editor = {X. Cheng and D. Z. Du},
     keywords = {Approximation algorithms, Combinatorial optimization, Graph algorithms, Steiner trees},
     note = {Survey article with new proofs},
     pages = {235--279},
     publisher = {Kluwer Academic Publishers},
     title = {Approximation Algorithms for the Steiner Tree Problem in Graphs},
     url = {http://publications.imp.fu-berlin.de/353/},
     year = {2001}
    }
  • C. Gröpl, S. Hougardy, T. Nierhoff, H.-J. Prömel, “Lower bounds for approximation algorithms for the Steiner tree problem”, 2001.
    cite this publication
    @inproceedings{fu_mi_publications355,
     abstract = {The Steiner tree problem asks for a shortest subgraph connecting a given set of
      terminals in a graph. It is known to be APX-complete, which means that no polynomial time
      approximation scheme can exist for this problem, unless P=NP. Currently, the best approximation
      algorithm for the Steiner tree problem has a performance ratio of {\ensuremath{<}}span
      class='mathrm'{\ensuremath{>}}1.55{\ensuremath{<}}/span{\ensuremath{>}}, whereas the corresponding
      lower bound is smaller than {\ensuremath{<}}span
      class='mathrm'{\ensuremath{>}}1.01{\ensuremath{<}}/span{\ensuremath{>}}. In this paper, we provide
      for several Steiner tree approximation algorithms lower bounds on their performance ratio that are
      much larger. For two algorithms that solve the Steiner tree problem on quasi-bipartite instances,
      we even prove lower bounds that match the upper bounds. Quasi-bipartite instances are of special
      interest, as currently all known lower bound reductions for the Steiner tree problem in graphs
      produce such instances.},
     author = {C. Gr{\"o}pl and S. Hougardy and T. Nierhoff and H.-J. Pr{\"o}mel},
     booktitle = {Proceedings of the 27th International Workshop on Graph-Theoretic Concepts in Computer
      Science (2001)},
     keywords = {Steiner trees, Approximation algorithms, Combinatorial optimization, Graph algorithms,
      Hypergraphs, set systems, and designs},
     publisher = {Springer Verlag},
     series = {LNCS},
     title = {Lower bounds for approximation algorithms for the Steiner tree problem},
     url = {http://publications.imp.fu-berlin.de/355/},
     year = {2001}
    }
  • C. Gröpl, H.-J. Prömel, A. Srivastav, “On the Evolution of the Worst-Case OBDD Size”, vol. 77, 2001.
    cite this publication
    @article{fu_mi_publications361,
     abstract = {We prove matching lower and upper bounds on the worst-case OBDD size of a Boolean
      function, revealing an interesting ocillating behaviour.},
     author = {C. Gr{\"o}pl and H.-J. Pr{\"o}mel and A. Srivastav},
     journal = {Information Processing Letters},
     keywords = {Binary Decision Diagrams},
     pages = {1--7},
     title = {On the Evolution of the Worst-Case OBDD Size},
     url = {http://publications.imp.fu-berlin.de/361/},
     volume = {77},
     year = {2001}
    }
  • D. H. Huson, A. L. Halpern, Z. Lai, E. W. Myers, K. Reinert, G. G. Sutton, “Comparing Assemblies using Fragments and Mate-pairs”, 2001.
    cite this publication
    @inproceedings{fu_mi_publications365,
     author = {D. H. Huson and A. L. Halpern and Z. Lai and E. W. Myers and K. Reinert and G. G.
      Sutton},
     booktitle = {Proceedings of the 1st Workshop on Algorithms Bioinformatics (WABI-01)},
     pages = {294--306},
     title = {Comparing Assemblies using Fragments and Mate-pairs},
     url = {http://publications.imp.fu-berlin.de/365/},
     year = {2001}
    }
  • D. H. Huson, K. Reinert, S. A. Kravitz, K. A. Remington, A. L. Delcher, I. M. Dew, M. J. Flanigan, A. L. Halpern, Z. Lai, C. M. Mobarry, G. G. Sutton, E. W. Myers, “Design of a compartmentalized Shotgun Assembler for the Human Genome”, 2001.
    cite this publication
    @inproceedings{fu_mi_publications366,
     author = {D. H. Huson and K. Reinert and S. A. Kravitz and K. A. Remington and A. L. Delcher and I.
      M. Dew and M. J. Flanigan and A. L. Halpern and Z. Lai and C. M. Mobarry and G. G. Sutton and E.
      W. Myers},
     booktitle = {Proceedings of the Ninth International Conference on Intelligent Systems for Molecular
      Biology (ISMB-01)},
     pages = {132--139},
     title = {Design of a compartmentalized Shotgun Assembler for the Human Genome},
     url = {http://publications.imp.fu-berlin.de/366/},
     year = {2001}
    }
  • D. H. Huson, K. Reinert, E. W. Myers, “The Greedy Path-Merging Algorithm for Sequence Assembly”, 2001.
    cite this publication
    @inproceedings{fu_mi_publications368,
     author = {D. H. Huson and K. Reinert and E. W. Myers},
     booktitle = {Proceedings of the Fifth Annual International Conference on Computational Molecular
      Biology (RECOMB-01)},
     pages = {157--163},
     title = {The Greedy Path-Merging Algorithm for Sequence Assembly},
     url = {http://publications.imp.fu-berlin.de/368/},
     year = {2001}
    }
  • R. J. Turner, K. Chaturvedi, N. J. Edwards, A. L. Halpern, D. H. Huson, O. Kohlbacher, J. R. Miller, K. Reinert, K. A. Remington, R. Schwartz, B. Walenz, S. Yooseph, S. Istrail, “Visualization Challenges for a New Cyberpharmaceutical Computing”, 2001.
    cite this publication
    @inproceedings{fu_mi_publications410,
     author = {R. J. Turner and K. Chaturvedi and N. J. Edwards and A. L. Halpern and D. H. Huson and O.
      Kohlbacher and J. R. Miller and K. Reinert and K. A. Remington and R. Schwartz and B. Walenz and
      S. Yooseph and S. Istrail},
     booktitle = {IEEE 2001 Symposium on Parallel and Large-Data Visualization and Graphics},
     note = {Keynote address},
     pages = {7--18},
     title = {Visualization Challenges for a New Cyberpharmaceutical Computing},
     url = {http://publications.imp.fu-berlin.de/410/},
     year = {2001}
    }
  • J. C. Venter, M. D. Adams, E. W. Myers, K. Reinert, . et al, “The Sequence of the Human Genome”, vol. 291, iss. 5507, 2001.
    cite this publication
    @article{fu_mi_publications411,
     abstract = {A 2.91-billion base pair (bp) consensus sequence of the euchromatic portion of the
      human genome was generated by the whole-genome shotgun sequencing method. The 14.8-billion bp DNA
      sequence was generated over 9 months from 27,271,853 high-quality sequence reads (5.11-fold
      coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals.
      Two assembly strategies{--}a whole-genome assembly and a regional chromosome assembly{--}were
      used, each combining sequence data from Celera and the publicly funded genome effort. The public
      data were shredded into 550-bp segments to create a 2.9-fold coverage of those genome regions that
      had been sequenced, without including biases inherent in the cloning and assembly procedure used
      by the publicly funded group. This brought the effective cov- erage in the assemblies to
      eightfold, reducing the number and size of gaps in the final assembly over what would be obtained
      with 5.11-fold coverage. The two assembly strategies yielded very similar results that largely
      agree with independent mapping data. The assemblies effectively cover the euchromatic regions of
      the human chromosomes. More than 90\% of the genome is in scaffold assemblies of 100,000 bp or
      more, and 25\% of the genome is in scaffolds of 10 million bp or larger. Analysis of the genome
      sequence revealed 26,588 protein-encoding transcripts for which there was strong corroborating
      evidence and an additional},
     author = {J. C. Venter and M. D. Adams and E. W. Myers and K. Reinert and . et al},
     journal = {Science},
     keywords = {ASSEMBLY},
     number = {5507},
     pages = {1304--1351},
     title = {The Sequence of the Human Genome},
     url = {http://publications.imp.fu-berlin.de/411/},
     volume = {291},
     year = {2001}
    }

2000

  • “The Genome Sequence of Drosophila melanogaster”, vol. 287, iss. 5461, 2000.
    cite this publication
    @article{fu_mi_publications324,
     journal = {Science},
     keywords = {ASSEMBLY},
     number = {5461},
     pages = {2185--2195},
     title = {The Genome Sequence of Drosophila melanogaster},
     url = {http://publications.imp.fu-berlin.de/324/},
     volume = {287},
     year = {2000}
    }
  • G. Baudis, C. Gröpl, S. Hougardy, T. Nierhoff, H.-J. Prömel, “Approximating Minimum Spanning Sets in Hypergraphs and Polymatroids”, 2000.
    cite this publication
    @techreport{fu_mi_publications329,
     author = {G. Baudis and C. Gr{\"o}pl and S. Hougardy and T. Nierhoff and H.-J. Pr{\"o}mel},
     institution = {Humboldt-University Berlin},
     keywords = {Hypergraphs, set systems, and designs, Steiner trees, Approximation algorithms,
      Colouring, packing and covering, Combinatorial optimization, Graph algorithms},
     note = {This paper was already accepted for ICALP 2000 but we did not present it since later we
      were informed that the main result had already been proven in a different way.},
     title = {Approximating Minimum Spanning Sets in Hypergraphs and Polymatroids},
     type = {Technical Report},
     url = {http://publications.imp.fu-berlin.de/329/},
     year = {2000}
    }
  • J. D. Kececioglu, H.-P. Lenhof, K. Mehlhorn, K. Reinert, M. Vingron, “A Polyhedral Approach to Sequence Alignment Problems”, vol. 104, 2000.
    cite this publication
    @article{fu_mi_publications370,
     author = {J. D. Kececioglu and H.-P. Lenhof and K. Mehlhorn and K. Reinert and M. Vingron},
     journal = {Discrete Applied Mathematics},
     pages = {143--186},
     title = {A Polyhedral Approach to Sequence Alignment Problems},
     url = {http://publications.imp.fu-berlin.de/370/},
     volume = {104},
     year = {2000}
    }
  • M. Lermen, K. Reinert, “The Practical Use of the A* Algorithm for Exact Multiple Sequence Alignment”, 2000.
    cite this publication
    @article{fu_mi_publications383,
     author = {M. Lermen and K. Reinert},
     journal = {Journal of Computational Biology},
     pages = {655--671},
     title = {The Practical Use of the A* Algorithm for Exact Multiple Sequence Alignment},
     url = {http://publications.imp.fu-berlin.de/383/},
     year = {2000}
    }
  • E. W. Myers, G. G. Sutton, A. L. Delcher, D. P. Dew, M. J. Flanigan, S. A. Kravitz, C. M. Mobarry, K. Reinert, K. A. Remington, E. L. Anson, R. Bolanos, H.-H. Chou, C. M. Jordan, A. L. Halpern, S. Lonardi, E. M. Beasly, R. C. Brandon, L. Chen, P. J. Dunn, Z. Lai, Y. Liang, D. R. Nusskern, M. Zhan, Q. Zhang, X. H. Zheng, G. M. Rubin, M. D. Adams, J. C. Venter, “A Whole-Genome Assembly of Drosophila”, vol. 287, iss. 5461, 2000.
    cite this publication
    @article{fu_mi_publications388,
     author = {E. W. Myers and G. G. Sutton and A. L. Delcher and D. P. Dew and M. J. Flanigan and S. A.
      Kravitz and C. M. Mobarry and K. Reinert and K. A. Remington and E. L. Anson and R. Bolanos and
      H.-H. Chou and C. M. Jordan and A. L. Halpern and S. Lonardi and E. M. Beasly and R. C. Brandon
      and L. Chen and P. J. Dunn and Z. Lai and Y. Liang and D. R. Nusskern and M. Zhan and Q. Zhang and
      X. H. Zheng and G. M. Rubin and M. D. Adams and J. C. Venter},
     journal = {Science},
     keywords = {ASSEMBLY},
     number = {5461},
     pages = {2196--2203},
     title = {A Whole-Genome Assembly of Drosophila},
     url = {http://publications.imp.fu-berlin.de/388/},
     volume = {287},
     year = {2000}
    }
  • K. Reinert, J. Stoye, T. Will, “An Iterative Methods for Faster Sum-of-Pairs Multiple Sequence Alignment”, vol. 16, iss. 9, 2000.
    cite this publication
    @article{fu_mi_publications400,
     author = {K. Reinert and J. Stoye and T. Will},
     journal = {BIOINFORMATICS},
     number = {9},
     pages = {808--814},
     title = {An Iterative Methods for Faster Sum-of-Pairs Multiple Sequence Alignment},
     url = {http://publications.imp.fu-berlin.de/400/},
     volume = {16},
     year = {2000}
    }

1999

  • C. Gröpl, “Binary Decision Diagrams for Random Boolean Functions”, 1999.
    cite this publication
    @unpublished{fu_mi_publications349,
     abstract = {(deutsche Zusammenfassung siehe unten)\&lt;p\&gt; Binary Decision Diagrams (BDDs) are a
      data structure for Boolean functions which are also known as branching programs. In ordered binary
      decision diagrams (OBDDs), the tests have to obey a fixed variable ordering. In free binary
      decision diagrams (FBDDs), each variable can be tested at most once. The efficiency of new
      variants of the BDD concept is usually demonstrated with spectacular (worst-case) examples. We
      pursue another approach and compare the representation sizes of almost all Boolean functions.
      Whereas I. Wegener proved that for `most' values of n the expected OBDD size of a random Boolean
      function of n variables is equal to the worst-case size up to terms of lower order, we show that
      this is not the case for n within intervals of constant length around the values n = 2h + h.
      Furthermore, ranges of n exist for which minimal FBDDs are almost always at least a constant
      factor smaller than minimal OBDDs. Our main theorems have doubly exponentially small probability
      bounds (in n). We also investigate the evolution of random OBDDs and their worst-case size,
      revealing an oscillating behaviour that explains why certain results cannot be improved in
      general. \&lt;p\&gt; \&lt;b\&gt;Zusammenfassung:\&lt;/b\&gt;\&lt;p\&gt; Binary Decision Diagrams
      (BDDs) sind eine Datenstruktur f{\"u}r Boolesche Funktionen, die auch unter dem Namen branching
      program bekannt ist. In ordered binary decision diagrams (OBDDs) m{\"u}ssen die Tests einer festen
      Variablenordnung gen{\"u}gen. In free binary decision diagrams (FBDDs) darf jede Variable
      h{\"o}chstens einmal getestet werden. Die Effizienz neuer Varianten des BDD-Konzepts wird
      gew{\"o}hnlich anhand spektakul{\"a}rer (worst-case) Beispiele aufgezeigt. Wir verfolgen einen
      anderen Ansatz und vergleichen die Darstellungsgr{\"o}{\ss}en f{\"u}r fast alle Booleschen
      Funktionen. W{\"a}hrend I. Wegener bewiesen hat, da{\ss} f{\"u}r die `meisten' n die erwartete
      OBDD-Gr{\"o}{\ss}e einer zuf{\"a}lligen Booleschen Funktion von n Variablen gleich der worst-case
      Gr{\"o}{\ss}e bis auf Terme kleinerer Ordnung ist, zeigen wir da{\ss} dies nicht der Fall ist
      f{\"u}r n innerhalb von Intervallen konstanter L{\"a}nge um die Werte n = 2h + h. Ferner gibt es
      Bereiche von n, in denen minimale FBDDs fast immer um mindestens einen konstanten Faktor kleiner
      sind als minimale OBDDs. Unsere Haupts{\"a}tze ha ben doppelt exponentielle Wahrschein-
      lichkeitsschranken (in n). Au{\ss}erdem untersuchen wir die Entwicklung zuf{\"a}lliger OBDDs und
      ihrer worst-case Gr{\"o}{\ss}e und decken dabei ein oszillierendes Verhalten auf, das erkl{\"a}rt,
      warum gewisse Aussagen im allgemeinen nicht verst{\"a}rkt werden k{\"o}nnen.
      \&lt;p\&gt;Schlagw{\"o}rter:\&lt;p\&gt; Bin{\"a}res Entscheidungsdiagramm, Boolesche
      Funktion,probabilistische Analyse, Shannon Effekt.},
     author = {C. Gr{\"o}pl},
     keywords = {Binary decision diagram, Boolean function, probabilistic analysis, Shannon effect},
     school = {Humboldt-Universit{\"a}t zu Berlin},
     title = {Binary Decision Diagrams for Random Boolean Functions},
     url = {http://publications.imp.fu-berlin.de/349/},
     year = {1999}
    }
  • H.-P. Lenhof, B. Morgenstern, K. Reinert, “An exact solution for the segment-to-segment multiple sequence alignment problem”, vol. 15, iss. 3, 1999.
    cite this publication
    @article{fu_mi_publications381,
     author = {H.-P. Lenhof and B. Morgenstern and K. Reinert},
     journal = {BIOINFORMATICS},
     number = {3},
     pages = {203--210},
     title = {An exact solution for the segment-to-segment multiple sequence alignment problem},
     url = {http://publications.imp.fu-berlin.de/381/},
     volume = {15},
     year = {1999}
    }

1998

  • C. Gröpl, H.-J. Prömel, A. Srivastav, D. Korb, Ch. Meinel, M. Morvan, “Size and Structure of Random Ordered Binary Decision Diagrams (Extended Abstract)”, iss. 1373, 1998.
    cite this publication
    @inproceedings{fu_mi_publications359,
     address = {Berlin, Heidelberg, New York},
     author = {C. Gr{\"o}pl and H.-J. Pr{\"o}mel and A. Srivastav},
     booktitle = {STACS 98},
     editor = {D. Korb and Ch. Meinel and M. Morvan},
     keywords = {VLSI-Design and layout, Hardware verification, Random graphs},
     number = {1373},
     pages = {238--248},
     publisher = {Springer Verlag},
     series = {Lecture Notes in Computer Science},
     title = {Size and Structure of Random Ordered Binary Decision Diagrams (Extended Abstract)},
     url = {http://publications.imp.fu-berlin.de/359/},
     year = {1998}
    }
  • C. Gröpl, M. Skutella, E. W. Mayr, H.-J. Prömel, A. Steger, “Parallel Repetition of MIP(2,1) Systems”, vol. 1367, 1998.
    cite this publication
    @incollection{fu_mi_publications363,
     author = {C. Gr{\"o}pl and M. Skutella},
     booktitle = {Lectures on Proof Verification and Approximation Algorithms},
     editor = {E. W. Mayr and H.-J. Pr{\"o}mel and A. Steger},
     keywords = {Theoretical computer science (other), Approximation algorithms, PCP and
      non-approximability},
     note = {The book grow out of a Dagstuhl Seminar, April 21-25, 1997},
     pages = {161--177},
     publisher = {Springer},
     series = {Lecture Notes in Computer Science},
     title = {Parallel Repetition of MIP(2,1) Systems},
     url = {http://publications.imp.fu-berlin.de/363/},
     volume = {1367},
     year = {1998}
    }
  • H.-P. Lenhof, K. Reinert, M. Vingron, “A polyhedral approach to RNA sequence structure alignment”, 1998.
    cite this publication
    @inproceedings{fu_mi_publications380,
     author = {H.-P. Lenhof and K. Reinert and M. Vingron},
     booktitle = {Proceedings of the Second Annual International Conference on Computational Molecular
      Biology (RECOMB-98)},
     pages = {153--162},
     title = {A polyhedral approach to RNA sequence structure alignment},
     url = {http://publications.imp.fu-berlin.de/380/},
     year = {1998}
    }
  • H.-P. Lenhof, K. Reinert, M. Vingron, “A Polyhedral Approach to RNA Sequence Structure Alignment”, vol. 5, iss. 3, 1998.
    cite this publication
    @article{fu_mi_publications382,
     author = {H.-P. Lenhof and K. Reinert and M. Vingron},
     journal = {Journal of Computational Biology},
     number = {3},
     pages = {517--530},
     title = {A Polyhedral Approach to RNA Sequence Structure Alignment},
     url = {http://publications.imp.fu-berlin.de/382/},
     volume = {5},
     year = {1998}
    }

1997

  • M. Block, C. Gröpl, H. Preuss, H. J. Prömel, A. Srivastav, “Efficient ordering of state variables and transition relation partitions in symbolic model checking”, 1997.
    cite this publication
    @techreport{fu_mi_publications335,
     author = {M. Block and C. Gr{\"o}pl and H. Preuss and H. J. Pr{\"o}mel and A. Srivastav},
     institution = {Humboldt-Universit{\"a}t zu Berlin},
     keywords = {Randomized algorithms and probabilistic analysis, VLSI-Design and layout, Binary
      Decision Diagrams, Hardware verification, Local search and metaheuristics},
     title = {Efficient ordering of state variables and transition relation partitions in symbolic model
      checking},
     type = {Technical Report},
     url = {http://publications.imp.fu-berlin.de/335/},
     year = {1997}
    }
  • K. Reinert, H.-P. Lenhof, P. Mutzel, J. D. Kececioglu, “A branch-and-Cut algorithm for multiple sequence alignment ”, 1997.
    cite this publication
    @inproceedings{fu_mi_publications399,
     author = {K. Reinert and H.-P. Lenhof and P. Mutzel and J. D. Kececioglu},
     booktitle = {Proceedings of the First Annual International Conference on Computational Molecular
      Biology (RECOMB-97)},
     pages = {241--249},
     title = {A branch-and-Cut algorithm for multiple sequence alignment},
     url = {http://publications.imp.fu-berlin.de/399/},
     year = {1997}
    }

1996

  • P. G. Bradford, K. Reinert, “Lower Bounds for Row Minima Searching”, 1996.
    cite this publication
    @inproceedings{fu_mi_publications343,
     author = {P. G. Bradford and K. Reinert},
     booktitle = {Proceedings of the 23rd International Colloquium on Automata, Languages, and
      Programming 1996 (ICALP-96), LNCS 1099},
     pages = {454--465},
     title = {Lower Bounds for Row Minima Searching},
     url = {http://publications.imp.fu-berlin.de/343/},
     year = {1996}
    }
  • C. Gröpl, “Über Approximationsalgorithmen zur FĂ€rbung k-fĂ€rbbarer Graphen, die vektorchromatische Zahl und andere Varianten der vartheta-Funktion”, 1996-01.
    cite this publication
    @unpublished{fu_mi_publications350,
     address = {Forschungsinstitut f{\"u}r Diskrete Mathematik},
     author = {C. Gr{\"o}pl},
     keywords = {Approximation algorithms, Colouring, packing and covering},
     month = {January},
     school = {Rheinische Friedrich-Wilhelms-Universit{\"a}t Bonn},
     title = {{\"U}ber Approximationsalgorithmen zur F{\"a}rbung k-f{\"a}rbbarer Graphen, die
      vektorchromatische Zahl und andere Varianten der vartheta-Funktion},
     url = {http://publications.imp.fu-berlin.de/350/},
     year = {1996}
    }