{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T05:52:22Z","timestamp":1767851542420,"version":"3.49.0"},"reference-count":47,"publisher":"Oxford University Press (OUP)","issue":"23","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2006,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: 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.<\/jats:p>\n               <jats:p>Results: 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.<\/jats:p>\n               <jats:p>Availability: GATHER is available at<\/jats:p>\n               <jats:p>Contact: \u00a0j.nevins@duke.edu<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btl483","type":"journal-article","created":{"date-parts":[[2006,9,26]],"date-time":"2006-09-26T00:49:36Z","timestamp":1159231776000},"page":"2926-2933","source":"Crossref","is-referenced-by-count":267,"title":["GATHER: a systems approach to interpreting genomic signatures"],"prefix":"10.1093","volume":"22","author":[{"given":"Jeffrey T.","family":"Chang","sequence":"first","affiliation":[{"name":"Department of Molecular Genetics and Microbiology, Duke Institute for Genome Sciences and Policy, Duke University Medical Center \u00a0 Durham, NC 27710, USA"}]},{"given":"Joseph R.","family":"Nevins","sequence":"additional","affiliation":[{"name":"Department of Molecular Genetics and Microbiology, Duke Institute for Genome Sciences and Policy, Duke University Medical Center \u00a0 Durham, NC 27710, USA"}]}],"member":"286","published-online":{"date-parts":[[2006,6,29]]},"reference":[{"key":"2023012409221900200_b1","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1093\/bioinformatics\/btg455","article-title":"FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes","volume":"20","author":"Al-Shahrour","year":"2004","journal-title":"Bioinformatics"},{"key":"2023012409221900200_b2","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1038\/nrg1749","article-title":"Microarray data analysis: from disarray to consolidation, consensus","volume":"7","author":"Allison","year":"2006","journal-title":"Nat. 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