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PROTEINCHALLENGE: Crowd sourcing in proteomics analysis and software development

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  • Sarah F Martin, Kinetic Parameter Facility, Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, Storbritannien
  • Heiner Falkenberg, Molecular Proteomics Laboratory, Biological-Medical-Research Centre, Heinrich-Heine-University Düsseldorf, Tyskland
  • Thomas Franck Dyrlund, Danmark
  • Guennadi A Khoudoli, Wellcome Trust Centre for Gene Regulation and Expression, College of Life Sciences, University of Dundee, Storbritannien
  • Craig J Mageean, Physiological laboratory, Institute for Translational Research, University of Liverpool, Storbritannien
  • Rune Linding, Danmarks Tekniske Universitet, Danmark
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.
TidsskriftJournal of Proteomics
Sider (fra-til)41-46
Antal sider6
StatusUdgivet - 2 aug. 2013

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