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Broad researchers earn kudos for software

GenePattern, a gene expression analysis software package developed by researchers from the Broad Institute, has received an Editor's Choice award from Bio-IT World, an award-winning technology publication.

Bio-IT World held its 2005 Best Practices celebration on June 28 in Washington, D.C. GenePattern, a freely available application, was selected from 33 submissions by a panel of computational biology experts. Submissions for the awards came from academic institutions and pharmaceutical and biotech companies.

"We are thrilled by this honor. Improving research practices is one of GenePattern's basic goals," said Michael Reich, manager of cancer informatics development and group leader for GenePattern. "As this tool helps accelerate genomic research, we look forward to its results--a quickened pace of scientific discovery and insight into biological processes and the causes of disease."

The GenePattern software package allows researchers to use a wide variety of methodologies to analyze gene expression data. It is also part of a larger architecture that addresses more general challenges in computational genomic research: the need to add new analysis tools quickly and easily, the need to reproduce the results of complex analyses that require the coordination of different tools, and the need for a range of interfaces that make analyses accessible to nonprogramming researchers without limiting the full power of a tool for more experienced users.

"This is a well-deserved reward for the GenePattern team," said Jill Mesirov, principal investigator and director of Computational Biology and Bioinformatics at the Broad Institute, a partnership among MIT, Harvard and affiliated hospitals and the Whitehead Institute for Biomedical Research. "They made our vision for GenePattern--ease of use, interoperability, reproducibility and flexibility--a reality."

In addition to Mesirov and Reich, members of the GenePattern development team include Gad Getz, Josh Gould, Charlotte Henson, Jim Lerner, Ted Liefeld, Stefano Monti, Ken Ross, Pablo Tamayo and Aravind Subramanian.

The work was supported by the National Institutes of Health.

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