"Self Organizing Maps" Help Analyze Thousands Of Genes

Using a sophisticated computer algorithm, a team of scientists at the Whitehead Institute has designed a new technique to analyze the massive amounts of data generated by DNA microarrays, also known as DNA chips. This technique will help scientists decipher how our 100,000 genes work together to keep us healthy and how diseases result when they fail.

"DNA arrays have revolutionized DNA analysis by allowing us to observe the activities of thousands of genes simultaneously," says Todd Golub, research scientist at the Whitehead/MIT Center for Genome Research. "But until now, it's been really difficult to interpret this extraordinarily complex raw data. Our technique is among the first in a new generation of tools that will speed up the analysis of the enormous amounts of genetic data emerging from laboratories worldwide."

Dr. Golub and his colleagues at the Whitehead Institute, Dana-Farber Cancer Institute, Dartmouth Medical School, and the Massachusetts Institute of Technology, report their technique in the March 16 issue of the Proceedings of the National Academy of Sciences. The Whitehead/MIT Center for Genome Research is one of the flagship centers of the U.S. Human Genome Project, the effort to determine the 3 billion letters that make up the human blueprint.

"The core of the technique is an algorithm, called a self-organizing map (SOM), that takes advantage of the fact that many genes in a cell behave similarly," explains Pablo Tamayo, the lead author of the paper and research scientist at the Whitehead Institute. "Instead of having 2,000 individual genes, all doing different things, you might have 25 groups of genes doing similar things."

Tamayo compares the final product of the SOM to an executive summary for CEOs. Rather than having to read every page of a 1,000-page report, CEOs can get an overview of the report by simply reading the summary. "It's impossible to visually inspect every gene," he says. "This method produces a qu

Contact: Stefanie Doebler
Whitehead Institute for Biomedical Research

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