{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T07:36:15Z","timestamp":1762673775947},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"15","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Results: We have developed LeTICE (Learning Transcriptional networks from the Integration of ChIP\u2013chip and Expression data), an algorithm for learning a transcriptional network from ChIP\u2013chip and expression data. The network is specified by a binary matrix of transcription factor (TF)\u2013gene interactions partitioning genes into modules and a background of genes that are not involved in the transcriptional regulation. We define a likelihood of a network, and then search for the network optimizing the likelihood.<\/jats:p>\n               <jats:p>We applied LeTICE to the location and expression data from yeast cells grown in rich media to learn the transcriptional network specific to the yeast cell cycle. It found 12 condition-specific TFs and 15 modules each of which is highly represented with functions related to particular phases of cell-cycle regulation.<\/jats:p>\n               <jats:p>Availability: Our algorithm is available at http:\/\/linus.nci.nih.gov\/Data\/YounA\/LeTICE.zip<\/jats:p>\n               <jats:p>Contact: \u00a0youna2@mail.nih.gov<\/jats:p>\n               <jats:p>Supplementary Information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq289","type":"journal-article","created":{"date-parts":[[2010,6,5]],"date-time":"2010-06-05T02:21:06Z","timestamp":1275704466000},"page":"1879-1886","source":"Crossref","is-referenced-by-count":14,"title":["Learning transcriptional networks from the integration of ChIP\u2013chip and expression data in a non-parametric model"],"prefix":"10.1093","volume":"26","author":[{"given":"Ahrim","family":"Youn","sequence":"first","affiliation":[{"name":"1 National Cancer Institute, Bethesda, MD, 2Institute for Systems Biology and 3Department of Statistics, University of Washington, Seattle, WA, USA"}]},{"given":"David J.","family":"Reiss","sequence":"additional","affiliation":[{"name":"1 National Cancer Institute, Bethesda, MD, 2Institute for Systems Biology and 3Department of Statistics, University of Washington, Seattle, WA, USA"}]},{"given":"Werner","family":"Stuetzle","sequence":"additional","affiliation":[{"name":"1 National Cancer Institute, Bethesda, MD, 2Institute for Systems Biology and 3Department of Statistics, University of Washington, Seattle, WA, USA"}]}],"member":"286","published-online":{"date-parts":[[2010,6,4]]},"reference":[{"key":"2023012507583262300_B1","doi-asserted-by":"crossref","first-page":"993","DOI":"10.1016\/0092-8674(93)90722-3","article-title":"Mechanisms that help the yeast cell cycle clock tick: G2 cyclins transcriptionally activate G2 cyclins and repress G1 cyclins","volume":"74","author":"Amon","year":"1993","journal-title":"Cell"},{"key":"2023012507583262300_B2","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1038\/nbt890","article-title":"Computational discovery of gene modules and regulatory networks","volume":"21","author":"Bar-Joseph","year":"2003","journal-title":"Nat. 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