Crowdsourcing of Biomedical Research
Medical, Health Informatics and Computational Biology Accomplishment | 2008 - 2015
IBM researcher: Gustavo Stolovitzky
Where the work was done: IBM T.J. Watson Research Center
What we accomplished: IBM's DREAM and IMPROVER Projects have pioneered crowdsourcing approaches for biomedical research, organizing the computational field to address important problems of validation of systems biology methods and models, especially for gene network inference as described in PNAS 2010: Revealing strengths and weaknesses of methods for gene network inference (347 citations, 1/28/2016) and Nature Methods 2010: Wisdom of crowds for robust gene network inference. (380 citations, 1/28/2016).
New high-throughput technologies have created biomedical datasets of unprecedented size and complexity. This rapid pace outstrips the capabilities of traditional peer-reviewed scientific methods and requires new paradigms that more quickly produce verified methods and data-driven findings. We have pioneered crowdsourcing-based approaches to critically assess complex analytic workflows using "wisdom of crowds" and accelerating the pace of scientific discovery, while additionally fostering the creation of communities around the most pressing biomedical problems. Our DREAM methodology harnesses "collaborative competition" and crowdsourcing in the form of open challenges, enticing the research community to verify their algorithms against carefully chosen benchmarks.
Related link: Crowdsourcing to Experts: The DREAM Challenges (Biomedical Computation Review, June 3, 2015.)
Image credit: IBM Research