FU Bioinformatics – German-Turkish Cooperation

FU Bioinformatics – German-Turkish Cooperation

FU Bioinformatics co-organized the first International Workshop on MS-Based Proteomics, Bioinformatics and Health Informatics with Turkish partners in Izmir

News from Jul 09, 2014

Together with the Izmir Institute of Technology and Hacettepe University, the FU Berlin organized the first International Workshop on MS-Based Proteomics, Bioinformatics and Health Informatics.

german-turkish_plakat

With funding from German-Turkish collaboration funds and local partners the workshop successfully initiated a lively exchange between German and Turkish groups working in MS-based Proteome research. The three day program included speakers from both countries, augmented by international partners from the USA, Canada, and Switzerland.

german-turkish_consul+reinert
(from left: Prof. Talat Yalcin, IZTECH – Thomas Gerlach, Consul General of Germany – Prof. Knut Reinert, FUB)

The German Consul General Thomas Gerlach recognized the workshop as an important contribution to the German-Turkish Year of Research, Education and Innovation.

Papers at ECCB 2014

The Reinert lab and collaborators presented two papers at the 14th European Conference on Computational biology in Strassbourg.

Hannes Hauswedell from our group presented
“Lambda: the local aligner for massive biological data [1] while Marcel Schulz from the Max-Planck in Saarbrücken presented “Fiona: a parallel and automatic strategy for read error correction” [2].

[1] [doi] H. Hauswedell, J. Singer, and K. Reinert, “Lambda: the local aligner for massive biological data,” Bioinformatics (oxford, england), vol. 30, iss. 17, p. i349–i355, 2014.
[Bibtex]
@article{Hauswedell:2014bt,
author = {Hauswedell, Hannes and Singer, Jochen and Reinert, Knut},
title = {{Lambda: the local aligner for massive biological data}},
journal = {Bioinformatics (Oxford, England)},
year = {2014},
volume = {30},
number = {17},
pages = {i349--i355},
month = sep,
publisher = {Oxford University Press},
affiliation = {Department of Mathematics and Computer Science, Freie Universit{\"a}t Berlin, Takustr. 9, 14195 Berlin, Germany.},
doi = {10.1093/bioinformatics/btu439},
pmid = {25161219},
pmcid = {PMC4147892},
language = {English},
read = {Yes},
rating = {0},
date-added = {2014-09-08T12:33:47GMT},
date-modified = {2014-09-08T12:36:10GMT},
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.},
url = {http://bioinformatics.oxfordjournals.org/content/30/17/i349.full},
local-url = {file://localhost/Users/reinert/Dropbox/Library.papers3/Files/94/9488230A-A39B-4CC4-9E72-D226E28C7C90},
file = {{9488230A-A39B-4CC4-9E72-D226E28C7C90:/Users/reinert/Dropbox/Library.papers3/Files/94/9488230A-A39B-4CC4-9E72-D226E28C7C90:application/pdf;9488230A-A39B-4CC4-9E72-D226E28C7C90:/Users/reinert/Dropbox/Library.papers3/Files/94/9488230A-A39B-4CC4-9E72-D226E28C7C90:application/pdf}},
uri = {\url{papers3://publication/doi/10.1093/bioinformatics/btu439}}
}
[2] [doi] M. H. Schulz, D. Weese, M. Holtgrewe, V. Dimitrova, S. Niu, K. Reinert, and H. Richard, “Fiona: a parallel and automatic strategy for read error correction,” Bioinformatics (oxford, england), vol. 30, iss. 17, p. i356–i363, 2014.
[Bibtex]
@article{Schulz:2014dm,
author = {Schulz, Marcel H and Weese, David and Holtgrewe, Manuel and Dimitrova, Viktoria and Niu, Sijia and Reinert, Knut and Richard, Hugues},
title = {{Fiona: a parallel and automatic strategy for read error correction}},
journal = {Bioinformatics (Oxford, England)},
year = {2014},
volume = {30},
number = {17},
pages = {i356--i363},
month = sep,
publisher = {Oxford University Press},
affiliation = {'Multimodal Computing and Interaction', Saarland University {\&} Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbr{\"u}cken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universit{\"a}t Berlin, 14195 Berlin, Germany, Universit{\'e} Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France 'Multimodal Computing and Interaction', Saarland University {\&} Department for Computational Biology and Applied Computing, Max Planck Institute for Informatics, Saarbr{\"u}cken, 66123 Saarland, Germany, Ray and Stephanie Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, 15206 PA, USA, Department of Mathematics and Computer Science, Freie Universit{\"a}t Berlin, 14195 Berlin, Germany, Universit{\'e} Pierre et Marie Curie, UMR7238, CNRS-UPMC, Paris, France and CNRS, UMR7238, Laboratory of Computational and Quantitative Biology, Paris, France.},
doi = {10.1093/bioinformatics/btu440},
pmid = {25161220},
pmcid = {PMC4147893},
language = {English},
read = {Yes},
rating = {0},
date-added = {2014-09-08T12:32:23GMT},
date-modified = {2014-09-08T12:36:10GMT},
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-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-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.fr
SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.},
url = {http://bioinformatics.oxfordjournals.org/content/30/17/i356.full},
local-url = {file://localhost/Users/reinert/Dropbox/Library.papers3/Files/75/75795684-ABC8-488D-BB7B-330F2F28B93C},
file = {{75795684-ABC8-488D-BB7B-330F2F28B93C:/Users/reinert/Dropbox/Library.papers3/Files/75/75795684-ABC8-488D-BB7B-330F2F28B93C:application/pdf;75795684-ABC8-488D-BB7B-330F2F28B93C:/Users/reinert/Dropbox/Library.papers3/Files/75/75795684-ABC8-488D-BB7B-330F2F28B93C:application/pdf}},
uri = {\url{papers3://publication/doi/10.1093/bioinformatics/btu440}}
}