| Nature Biotechnology
Prize-based Contests Can Provide Solutions to Computational Biology Problems
Advances in biotechnology have fueled the generation of unprecedented quantities of data across the life sciences. However, finding analysts who can address such "big data" problems effectively has become a significant research bottleneck. Historically, prize-based contests have had striking success in attracting unconventional individuals who can overcome difficult challenges. To determine whether this approach could solve a real big-data biologic algorithm problem, we used a complex immunogenomics problem as the basis for a two-week online contest broadcast to participants outside academia and biomedical disciplines. Participants in our contest produced over 600 submissions containing 89 novel computational approaches to the problem. Thirty submissions exceeded the benchmark performance of the U.S. National Institutes of Health's MegaBLAST. The best achieved both greater accuracy and speed (1,000 times greater). Here we show the potential of using online prize-based contests to access individuals without domain-specific backgrounds to address big-data challenges in the life sciences.
Lakhani, Karim R., Kevin Boudreau, Eva C. Guinan, Carliss Y. Baldwin, Alan MacCormack, Eric Lonstein, Mike Lydon, and Ramy A Arnaout. "Prize-based Contests Can Provide Solutions to Computational Biology Problems." Nature Biotechnology 31, no. 2 (February, 2013): 108–111.