Crowdsourcing biomedical research: Leveraging communities as innovation engines

Julio Saez-Rodriguez, James C. Costello, Stephen H. Friend, Michael R. Kellen, Lara Mangravite, Pablo Meyer, Thea Norman, Gustavo Stolovitzky

Research output: Contribution to journalReview articlepeer-review

103 Scopus citations

Abstract

The generation of large-scale biomedical data is creating unprecedented opportunities for basic and translational science. Typically, the data producers perform initial analyses, but it is very likely that the most informative methods may reside with other groups. Crowdsourcing the analysis of complex and massive data has emerged as a framework to find robust methodologies. When the crowdsourcing is done in the form of collaborative scientific competitions, known as Challenges, the validation of the methods is inherently addressed. Challenges also encourage open innovation, create collaborative communities to solve diverse and important biomedical problems, and foster the creation and dissemination of well-curated data repositories.

Original languageEnglish
Pages (from-to)470-486
Number of pages17
JournalNature Reviews Genetics
Volume17
Issue number8
DOIs
StatePublished - 1 Aug 2016
Externally publishedYes

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