Briefs

STANFORD, Calif.--(BUSINESS WIRE)--Jan. 10, 2006--A new method to mine existing scientific data may provide a wealth of information about the interactions among genes, the environment and biological processes, say researchers at the Stanford University School of Medicine, Lucile Packard Children's Hospital and Harvard Medical School. Like panning for gold, they used the powerful technique to sift through millions of bits of unrelated information -- in this case, gene expression data from so-called microarray experiments -- to pinpoint genes likely to be involved in leukemia, aging, injury and muscle development.

Atul Butte is the first author of the study, which is published in the Jan. 6 online issue of Nature Biotechnology. ...

Butte and his Harvard co-author, Isaac Kohane, MD, PhD, used computer programs to automatically categorize the tens of thousands of microarray experiments in a single database based on the terms, or concepts, used by the submitter to describe the experiment. They then looked for findings shared by several experiments with similar concepts, such as tissue type, for example. Comparing results from many similar experiments allowed them to identify correlations that may not be statistically significant in just one experiment.

Butte and Kohane identified several previously unknown correlations: nine genes whose expression increased or decreased significantly with aging, two genes that are highly expressed in response to injury, and another gene in which the expression drops significantly in leukemic cells. They also confirmed these relationships by studying genes known to be associated with muscle tissue in both humans and mice.

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