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PMID: 17000751 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

GATHER: a systems approach to interpreting genomic signatures.

Bioinformatics (Oxford, England) ·Vol. 22 ·No. 23 ·2006-12-01 ·Pages 2926-33

Chang JT, Nevins JR

Abstract

Understanding the full meaning of the biology captured in molecular profiles, within the context of the entire biological system, cannot be achieved with a simple examination of the individual genes in the signature. To facilitate such an understanding, we have developed GATHER, a tool that integrates various forms of available data to elucidate biological context within molecular signatures produced from high-throughput post-genomic assays. Analyzing the Rb/E2F tumor suppressor pathway, we show that GATHER identifies critical features of the pathway. We further show that GATHER identifies common biology in a series of otherwise unrelated gene expression signatures that each predict breast cancer outcome. We quantify the performance of GATHER and find that it successfully predicts 90% of the functions over a broad range of gene groups. We believe that GATHER provides an essential tool for extracting the full value from molecular signatures generated from genome-scale analyses. GATHER is available at http://gather.genome.duke.edu/

MeSH Terms
Algorithms Chromosome Mapping/methods DNA Fingerprinting/methods Quantitative Trait Loci/genetics Sequence Analysis, DNA/methods Software Systems Biology/methods Systems Theory
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Chang Jeffrey T
Department of Molecular Genetics and Microbiology, Duke Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, NC 27710, USA.
Nevins Joseph R
Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4811
Published
2006-12-01
Epub
2006-00-25
Pages
2926-33
Language
English
Region
England
NLM ID
9808944
Subset
IM
Grants
NCI NIH HHS · 5-U54-CA112952 · United States
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