2009

  • [DOI] D. Weese, A. Emde, T. Rausch, A. Döring, and K. Reinert, “RazerS–fast read mapping with sensitivity control.,” Genome research, vol. 19, iss. 9, pp. 1646-1654, 2009.
    [Bibtex]
    @article{Weese:2009iw,
    author = {Weese, David and Emde, A and Rausch, T and D{"o}ring, Andreas and Reinert, Knut},
    title = {{RazerS--fast read mapping with sensitivity control.}},
    journal = {Genome research},
    year = {2009},
    volume = {19},
    number = {9},
    pages = {1646--1654},
    month = sep,
    affiliation = {Department of Computer Science, Free University of Berlin, 14195 Berlin, Germany. weese@inf.fu-berlin.de},
    doi = {10.1101/gr.088823.108},
    pmid = {19592482},
    pmcid = {PMC2752123},
    language = {English},
    read = {Yes},
    rating = {0},
    date-added = {2009-08-14T13:54:02GMT},
    date-modified = {2016-01-14T20:14:40GMT},
    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, efficient algorithms and implementations are crucial for this task. We present an efficient 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-defined loss rate at higher speeds. Given the loss rate, we present an 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.},
    url = {http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=19592482&retmode=ref&cmd=prlinks},
    local-url = {file://localhost/Users/reinert/Dropbox/Library.papers3/Articles/2009/Weese/Genome%20Res.%202009%20Weese.pdf},
    file = {{Genome Res. 2009 Weese.pdf:/Users/reinert/Dropbox/Library.papers3/Articles/2009/Weese/Genome Res. 2009 Weese.pdf:application/pdf}},
    uri = {url{papers3://publication/doi/10.1101/gr.088823.108}}
    }
  • [DOI] T. Rausch, S. Koren, G. Denisov, D. Weese, A. Emde, A. Döring, and K. Reinert, “A consistency-based consensus algorithm for de novo and reference-guided sequence assembly of short reads.,” Bioinformatics (oxford, england), vol. 25, iss. 9, pp. 1118-1124, 2009.
    [Bibtex]
    @article{Rausch:2009hq,
    author = {Rausch, T and Koren, Sergey and Denisov, G and Weese, David and Emde, A and D{"o}ring, Andreas and Reinert, Knut},
    title = {{A consistency-based consensus algorithm for de novo and reference-guided sequence assembly of short reads.}},
    journal = {Bioinformatics (Oxford, England)},
    year = {2009},
    volume = {25},
    number = {9},
    pages = {1118--1124},
    month = may,
    affiliation = {International Max Planck Research School for Computational Biology and Scientific Computing, Ihnestr. 63-73, Algorithmische Bioinformatik, Institut f{"u}r Informatik, Takustr. 9, 14195 Berlin, Germany. rausch@inf.fu-berlin.de},
    doi = {10.1093/bioinformatics/btp131},
    pmid = {19269990},
    pmcid = {PMC2732307},
    language = {English},
    read = {Yes},
    rating = {0},
    date-added = {2009-03-11T08:51:34GMT},
    date-modified = {2016-01-14T20:14:42GMT},
    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.},
    url = {http://bioinformatics.oxfordjournals.org/cgi/content/short/25/9/1118},
    local-url = {file://localhost/Users/reinert/Dropbox/Library.papers3/Articles/2009/Rausch/Bioinformatics%202009%20Rausch.pdf},
    file = {{Bioinformatics 2009 Rausch.pdf:/Users/reinert/Dropbox/Library.papers3/Articles/2009/Rausch/Bioinformatics 2009 Rausch.pdf:application/pdf}},
    uri = {url{papers3://publication/doi/10.1093/bioinformatics/btp131}}
    }
  • T. Rausch and K. Reinert, “The problem solving handbook for computational biology and bioinformatics,” , L. S. Heath and N. Ramakrishnan, Eds., Springer, 2009.
    [Bibtex]
    @incollection{Rausch2009,
    author = {Rausch, T and Reinert, Knut},
    title = {{The problem solving handbook for computational biology and bioinformatics}},
    year = {2009},
    editor = {Heath, L S and Ramakrishnan, N},
    publisher = {Springer},
    rating = {0},
    date-added = {2013-09-04T14:04:09GMT},
    date-modified = {2015-07-12T09:51:09GMT},
    uri = {url{papers3://publication/uuid/A9C736AD-428B-4BD0-9E47-9FEBC190E3A9}}
    }
  • A. Emde, T. Rausch, A. Döring, and K. Reinert, “RazerStextemdashfast read mapping with sensitivity control,” Genome ldots, 2009.
    [Bibtex]
    @article{Emde:2009wq,
    author = {Emde, A and Rausch, T and D{"o}ring, Andreas and Reinert, Knut},
    title = {{RazerS{textemdash}fast read mapping with sensitivity control}},
    journal = {Genome {ldots}},
    year = {2009},
    rating = {0},
    date-added = {2015-09-08T22:50:00GMT},
    date-modified = {2015-11-26T15:38:49GMT},
    abstract = {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 ...
    },
    url = {http://genome.cshlp.org/content/19/9/1646.short},
    uri = {url{papers3://publication/uuid/FF1EEB49-88E0-4C15-B291-F9A5F896E20C}}
    }
2016-02-16T11:01:20+00:00