PROTEINCHALLENGE: Crowd sourcing in proteomics analysis and software development

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

Research output: Contribution to journalArticlepeer-review


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


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


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