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PROTEINCHALLENGE: Crowd sourcing in proteomics analysis and software development

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DOI

  • Sarah F Martin, Kinetic Parameter Facility, Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, United Kingdom
  • Heiner Falkenberg, Molecular Proteomics Laboratory, Biological-Medical-Research Centre, Heinrich-Heine-University Düsseldorf, Germany
  • Thomas Franck Dyrlund, Denmark
  • Guennadi A Khoudoli, Wellcome Trust Centre for Gene Regulation and Expression, College of Life Sciences, University of Dundee, United Kingdom
  • Craig J Mageean, Physiological laboratory, Institute for Translational Research, University of Liverpool, United Kingdom
  • Rune Linding, Cellular Signal Integration Group (C-SIG), Centre for Biological Sequence Analysis (CBS), Department of Systems Biology, Technical University of Denmark (DTU), Denmark
In large-scale proteomics studies there is a temptation, after months of experimental work, to plug resulting data into a convenient-if poorly implemented-set of tools, which may neither do the data justice nor help answer the scientific question. In this paper we have captured key concerns, including arguments for community-wide open source software development and "big data" compatible solutions for the future. For the meantime, we have laid out ten top tips for data processing. With these at hand, a first large-scale proteomics analysis hopefully becomes less daunting to navigate. However there is clearly a real need for robust tools, standard operating procedures and general acceptance of best practises. Thus we submit to the proteomics community a call for a community-wide open set of proteomics analysis challenges-PROTEINCHALLENGE-that directly target and compare data analysis workflows, with the aim of setting a community-driven gold standard for data handling, reporting and sharing. This article is part of a Special Issue entitled: EUPA 2012: NEW HORIZONS.
Original languageEnglish
JournalJournal of Proteomics
Volume88
Pages (from-to)41-46
Number of pages6
ISSN1874-3919
DOIs
Publication statusPublished - 2 Aug 2013

    Research areas

  • Crowd sourcing, Community challenge, Data analysis, Software, Benchmarking;

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