The Scientist chimes in with some fantastic coverage of the Sage-DREAM Breast Cancer Challenge.
Three of the better quotes follow, but it’s worth reading the whole thing!
Though teams from computational big hitters like IBM were early leaders, the winners were a small group from Columbia University’s School of Engineering led by electrical engineer turned computational biologist Dimitris Anastassio. Their model hinged on three gene signatures, previously identified by Anastassio’s research group to be associated with several cancers, that proved to be highly prognostic in breast cancer—so much so that their model predicts with 76 percent accuracy which of two breast cancer patients will live longer.
“Their solution was out-of-the-box,” said DREAM founder Gustavo Stolovitzky, who has overseen 24 open computational challenges over the last 6 years. “They were not prejudiced by the old way of doing things, by the same-old, same-old. This allowed them to take an approach that was completely novel and, as it turns out, the best solution.”
A testament to Friend’s belief that money is not driving participation, he and his colleagues did not offer a high-dollar bounty to the BCC winners. Rather, the prize was a publication in Science Translational Medicine—a reward that organizers refer to a “powerful intellectual currency,” Friend said. For the BCC, the journal’s editors scrapped the usual system of blind peer-review and instead selected reviewers to be embedded with the competition itself. The editors also helped develop criteria for determining the winning models; if these criteria were not met, there would have been no winner and no publication. Despite these stipulations, the publication-as-prize model was a ringing success, with the BCC attracting some 350 teams from 30 countries. And the winning team’s model met Science Translational Medicine’s criteria, earning itself a spot in the journal this past April.