{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:01:52Z","timestamp":1760954512579},"reference-count":0,"publisher":"Oxford University Press (OUP)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2003,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: In order to understand transcription regulation in a given prokaryotic genome, it is critical to identify operons, the fundamental units of transcription, in such species. While there are a growing number of organisms whose sequence and gene coordinates are known, by and large their operons are not known.<\/jats:p>\n               <jats:p>Results: We present a probabilistic approach to predicting operons using Bayesian networks. Our approach exploits diverse evidence sources such as sequence and expression data. We evaluate our approach on the Escherichia coli K-12 genome where our results indicate we are able to identify over 78% of its operons at a 10% false positive rate. Also, empirical evaluation using a reduced set of data sources suggests that our approach may have significant value for organisms that do not have as rich of evidence sources as E.coli.<\/jats:p>\n               <jats:p>Availability: Our E.coli K-12 operon predictions are available at http:\/\/www.biostat.wisc.edu\/gene-regulation<\/jats:p>\n               <jats:p>Contact: joebock@biostat.wisc.edu<\/jats:p>\n               <jats:p>* To whom correspondence should be addressed.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btg147","type":"journal-article","created":{"date-parts":[[2003,6,30]],"date-time":"2003-06-30T23:09:17Z","timestamp":1057014557000},"page":"1227-1235","source":"Crossref","is-referenced-by-count":70,"title":["A Bayesian network approach to operon prediction"],"prefix":"10.1093","volume":"19","author":[{"given":"Joseph","family":"Bockhorst","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark","family":"Craven","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Page","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jude","family":"Shavlik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeremy","family":"Glasner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2003,7,1]]},"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/19\/10\/1227\/48903806\/bioinformatics_19_10_1227.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/19\/10\/1227\/48903806\/bioinformatics_19_10_1227.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T15:50:50Z","timestamp":1674661850000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/19\/10\/1227\/184417"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003,7,1]]},"references-count":0,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2003,7,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btg147","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2003,7,1]]},"published":{"date-parts":[[2003,7,1]]}}}