PROTEINCHALLENGE: Crowd sourcing in proteomics analysis and software development

Sarah F. Martin, Heiner Falkenberg, Thomas Franck Dyrlund, Guennadi A. Khoudoli, Craig J. Mageean, Rune Linding

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    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: New Horizons and Applications for Proteomics [EuPA 2012].
    Original languageEnglish
    JournalJournal of Proteomics
    Pages (from-to)41-46
    Publication statusPublished - 2013


    • Crowd sourcing
    • Community challenge
    • Data analysis
    • Software
    • Benchmarking
    • Open source


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