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PROTEINCHALLENGE: Crowd sourcing in proteomics analysis and software development

Research output: Contribution to journalArticle

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

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Original languageEnglish
Pages (from-to)41-46
Number of pages6
JournalJournal of proteomics
Volume88
DOIs
Publication statusPublished - 1 Aug 2013

Abstract

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].

    Research areas

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

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