Berger; her former grad student Michael Baym PhD '09, who's now a visiting scholar in the MIT math department and a postdoc in systems biology at Harvard Medical School; and her current grad student Po-Ru Loh developed a way to mathematically represent the genomes of different species or of different individuals within a species such that the overlapping data is stored only once. A search of multiple genomes can thus concentrate on their differences, saving time.
"If I want to run a computation on my genome, it takes a certain amount of time," Baym explains. "If I then want to run the same computation on your genome, the fact that we're so similar means that I've already done most of the work."
In experiments on a database of 36 yeast genomes, the researchers compared their algorithm to one called BLAST, for Basic Local Alignment Search Tool, one of the most commonly used genomic-search algorithms in biology. In a search for a particular genetic sequence in only 10 of the yeast genomes, the new algorithm was twice as fast as BLAST; but in a search of all 36 genomes, it was four times as fast. That discrepancy will only increase as genomic databases grow larger, Berger explains.
The new algorithm would be useful in any application where the central question is, as Baym puts it: "I have a sequence; what is it similar to?" Identifying microbes is one example. The new algorithm could help clinicians determine causes of infections, or it could help biologists characterize "microbiomes," collections of microbes found in animal tissue or particular microenvironments; variations in the human microbiome have been implicated in a range of medical conditions. It could be used to characterize the microbes in particularly fertile or infertile soil, and it could even be used in forensics, to determine the geographical origins of physical ev
|Contact: Caroline McCall, MIT Media Relations|
Massachusetts Institute of Technology