Bio Data-Cruncher Hits Jackpot
Posted: Thu Oct 28, 2004 8:41 am
While surfing the internet not long ago, a Harvard biologist stumbled upon a pile of public research data including unpublished leftovers from an unresolved genetics study. It wasn't unusual: Data like that can be found all over the web.
But then 33-year-old biology professor Vamsi Mootha did something remarkable. Using a unique computational method, he mined the data and identified a gene underlying a rare but fatal pediatric disorder called Leigh syndrome, French-Canadian variant, or LSFC. Astonishingly, he did it in a single weekend.
Genius colleagues nationwide proclaimed Mootha one of their ilk when they read his results in the journal Nature Genetics. The MacArthur Foundation fellowship committee concurred, offering the biologist and internal medicine physician one of this year's 23 MacArthur "genius awards" and a $500,000 endowment to spend as he pleases.
It wasn't so much the individual gene discovery, however important, that drew the attention of the MacArthur selection committee, but Mootha's ability to translate vast datasets into useful biological and clinical insights.
For the rest of the story:
http://www.wired.com/news/print/0,1294,65474,00.html
But then 33-year-old biology professor Vamsi Mootha did something remarkable. Using a unique computational method, he mined the data and identified a gene underlying a rare but fatal pediatric disorder called Leigh syndrome, French-Canadian variant, or LSFC. Astonishingly, he did it in a single weekend.
Genius colleagues nationwide proclaimed Mootha one of their ilk when they read his results in the journal Nature Genetics. The MacArthur Foundation fellowship committee concurred, offering the biologist and internal medicine physician one of this year's 23 MacArthur "genius awards" and a $500,000 endowment to spend as he pleases.
It wasn't so much the individual gene discovery, however important, that drew the attention of the MacArthur selection committee, but Mootha's ability to translate vast datasets into useful biological and clinical insights.
For the rest of the story:
http://www.wired.com/news/print/0,1294,65474,00.html