Two recent research efforts highlight the potential of nontraditional computing advances on drug discovery and development. They illustrate alternative uses of social networks for data generation and analysis. And they tap the social network gift of appealing to people in applying distributed computing collaboration to big R&D problems.
Both projects answer a personal need among participants that motivates their involvement. In one case, it's the chance to compete; in the other, it's the ability to contribute unique and personal data to a larger cause.
In the multi-player online game FoldIt, competing players manipulate a protein structure as if they were solving a visual puzzle. The game uses humans' spatial reasoning skills to improve computational predictions of protein conformation. FoldIt predictions have been shown as good as or better than those of a traditional computational approach in seven of 10 test cases.
Separately, researchers collaborating with consumer genetics testing company 23andMe have tapped trait data collected through online surveys completed by consumers whose genetics had already been analyzed by the company. The researchers studied 22 traits in nearly 10,000 people. They identified single-nucleotide polymorphisms associated with six traits, and novel associations with four traits.
The projects were identified in a Nature Biotechnology poll of researchers concerning efforts that have influenced the direction of their work.
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