A self-taught data-miner from Baltimore outsmarted IBM’s Watson computing system—a Jeopardy! Champion—in a $500 competition aimed at developing new algorithms for predicting progression of the HIV virus. Chris Raimondi topped a field of 118 players in a contest hosted by Kaggle, whose predictive data-modeling platform is designed to attract many of the world’s brightest minds. The contest remains an example of how predictive data modeling could, and should, serve as a model for tackling some of the toughest problems in bioinformatics. Yet just 8% of the company’s scientific community have backgrounds in bioinformatics, biostatistics, and computational biology. And biopharma firms and institutes are concerned about making data public as well as not being able to fully capitalize on the outcome of such a contest. Do you think an open competition can aid life science research?
How helpful do you think a predictive data-modeling contest could be for biotech researchers?