PITTSBURGHA new computational tool developed by U.S. and Israeli scientists will help scientists exploit the massive databases of gene expression experimental results that have been created over the past decade. Researchers say it could uncover new links between diseases and treatments and provide new insights into biological processes.
The team, headed by Ziv Bar-Joseph of Carnegie Mellon University, reports in the October issue of the journal Nature Methods that the tool, called ExpressionBlast, enables searches based directly on experimental values, rather than keywords.
The researchers already have used ExpressionBlast to uncover intriguing clues about SIRT6, the first gene shown to extend lifespan in mice and thus a potentially important drug target. By mining experimental data stored in a public repository called the Gene Expression Omnibus (GEO) maintained by the National Center for Biotechnology Information, they found that SIRT6 may be involved with functions that include immune response, metabolism and the regulation of gender-specific genes.
"Because so little is known about SIRT6, it would be difficult to search the hundreds of thousands of GEO datasets using keywords and, without other guidance, it would be practically impossible to find other experiments with gene expression patterns similar to SIRT6," said Bar-Joseph, an associate professor of computational biology and machine learning. "ExpressionBlast enabled us to take SIRT6 gene expression data from just two mouse experiments and find other experimental data in GEO with similar expression patterns."
The tool is available online, http://www.expression.cs.cmu.edu/. The search engine enables researchers to search for expression patterns that are similar or opposite to their own results and can search within and across species.
Guy Zinman, Shoshana Naiman, Yariv Kanfi and Haim Cohen of Bar-Ilan Universi
|Contact: Byron Spice|
Carnegie Mellon University