Pattern recognition method zeroes in on genes that regulate cell's genetic...( ARLINGTON Va.Using a new technique for...)

Pattern recognition method zeroes in on genes that regulate cell's genetic machinery

ARLINGTON, Va.Using a new technique for recognizing patterns in biological databases, a team of U.S. and Israeli computer scientists and geneticists have developed a practical computational method that zeroes in on the genes responsible for controlling the genetic machinery of a cell.

In a paper published online May 12 by Nature Genetics, the researchers from Stanford University and Hebrew University and the Weizmann Institute in Israel report that their method revealed several previously unknown control, or regulatory, genes from Saccharomyces cerevisiae, better known as bakers yeast. The work was supported in part by an Information Technology Research grant from the National Science Foundation, the independent agency that supports basic research in all fields of science and engineering.

Daphne Koller, a computer science professor at Stanford, is leading an effort to develop general models for recognizing meaningful patterns that span many related databases. This unique ability to "mix and match" biological data sources gives the new method its power.

Ordinarily, regulatory genes are identified experimentally, not computationally. The new computational method makes the experimental process much more efficient. It identifies regulatory candidates for testing in the lab and predicts how each regulator will affect cellular activity. The demonstration on the yeast genome data discovered several possible new regulatory genes and the clusters they regulate, and the team has already confirmed three of the predictions in the lab.

The primary data source for the method is gene expression technology, which involves mixing probes for thousands of genes with a biological sample under specific conditions. The probes provide a detailed snapshot, called a microarray, of the genes active in those conditions. A typical experiment would produce microarrays for hundreds of different conditions to see which genes are expressed in each condition. '"/>

Contact: David Hart
dhart@nsf.gov
703-292-7737
National Science Foundation
12-May-2003

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