Leading the Way in Life Science Technologies

GEN Exclusives

More »

GEN News Highlights

More »
Jan 5, 2012

Predictive Data Modeling in Life Science Research Wins Support from GEN Poll Voters

  • Almost all respondents to a recent GEN poll think a predictive data-modeling contest would be at least of some use to them. With 60% saying it would be very helpful and another 33.3% somewhat helpful, respondents are attracted to open competitions like the one hosted by Kaggle to develop new algorithms for predicting progression of the HIV virus.

    In that competition, a self-taught data-miner from Baltimore outsmarted a team from IBM’s Thomas J. Watson research center, to capture the $500 prize. The contest shows 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 Kaggle scientific community has backgrounds in bioinformatics, biostatistics, and computational biology. And biopharma firms and institutes remain concerned about making data public as well as not being able to fully capitalize on the outcome of such a contest.

     



Be sure to take the GEN Poll

Scientifically Studying Ecstasy

MDMA (commonly known as the empathogen “ecstasy”) is classified as a Schedule 1 drug, which is reserved for compounds with no accepted medical use and a high abuse potential. Two researchers from Stanford, however, call for a rigorous scientific exploration of MDMA's effects to identify precisely how the drug works, the data from which could be used to develop therapeutic compounds.

Do you agree that ecstasy should be studied for its potential therapeutic benefits?

More »