{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T05:33:43Z","timestamp":1783748023373,"version":"3.55.0"},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2017,9,23]],"date-time":"2017-09-23T00:00:00Z","timestamp":1506124800000},"content-version":"vor","delay-in-days":1,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2015-03948"],"award-info":[{"award-number":["RGPIN-2015-03948"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","award":["384410"],"award-info":[{"award-number":["384410"]}],"id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U41HG007000"],"award-info":[{"award-number":["U41HG007000"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,2,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>Segway performs semi-automated genome annotation, discovering joint patterns across multiple genomic signal datasets. We discuss a major new version of Segway and highlight its ability to model data with substantially greater accuracy. Major enhancements in Segway 2.0 include the ability to model data with a mixture of Gaussians, enabling capture of arbitrarily complex signal distributions, and minibatch training, leading to better learned parameters.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Segway and its source code are freely available for download at http:\/\/segway.hoffmanlab.org. We have made available scripts (https:\/\/doi.org\/10.5281\/zenodo.802939) and datasets (https:\/\/doi.org\/10.5281\/zenodo.802906) for this paper\u2019s analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btx603","type":"journal-article","created":{"date-parts":[[2017,9,19]],"date-time":"2017-09-19T23:12:13Z","timestamp":1505862733000},"page":"669-671","source":"Crossref","is-referenced-by-count":38,"title":["Segway 2.0: Gaussian mixture models and minibatch training"],"prefix":"10.1093","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1009-6379","authenticated-orcid":false,"given":"Rachel C W","family":"Chan","sequence":"first","affiliation":[{"name":"Princess Margaret Cancer Centre, Toronto, ON, Canada"},{"name":"Engineering Physics Program, University of British Columbia, Vancouver, BC, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maxwell W","family":"Libbrecht","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric G","family":"Roberts","sequence":"additional","affiliation":[{"name":"Princess Margaret Cancer Centre, Toronto, ON, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey A","family":"Bilmes","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA"},{"name":"Department of Electrical Engineering, University of Washington, Seattle, WA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William Stafford","family":"Noble","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA"},{"name":"Department of Genome Sciences, University of Washington, Seattle, WA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael M","family":"Hoffman","sequence":"additional","affiliation":[{"name":"Princess Margaret Cancer Centre, Toronto, ON, Canada"},{"name":"Department of Computer Science, University of Toronto, Toronto, ON, Canada"},{"name":"Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2017,9,22]]},"reference":[{"key":"2023012712332585500_btx603-B1","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1038\/nmeth.1906","article-title":"ChromHMM: automating chromatin-state discovery and characterization","volume":"9","author":"Ernst","year":"2012","journal-title":"Nat. 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