title: Unsupervised pattern discovery in human chromatin structure through genomic segmentation.
abstract: We trained Segway, a dynamic Bayesian network method, simultaneously on chromatin data from multiple experiments, including positions of histone modifications, transcription-factor binding and open chromatin, all derived from a human chronic myeloid leukemia cell line. In an unsupervised fashion, we identified patterns associated with transcription start sites, gene ends, enhancers, transcriptional regulator CTCF-binding regions and repressed regions. Software and genome browser tracks are at http://noble.gs.washington.edu/proj/segway/.
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle, Washington, USA.
authors.forename: Michael M
authors.initials: MM
authors.lastname: Hoffman
authors.forename: Orion J
authors.initials: OJ
authors.lastname: Buske
authors.forename: Jie
authors.initials: J
authors.lastname: Wang
authors.forename: Zhiping
authors.initials: Z
authors.lastname: Weng
authors.forename: Jeff A
authors.initials: JA
authors.lastname: Bilmes
authors.forename: William Stafford
authors.initials: WS
authors.lastname: Noble
mesh_terms: D001499:Bayes Theorem; D002843:Chromatin / Q000235:genetics / Q000502:physiology*; D015894:Genome, Human; D006657:Histones / Q000235:genetics / Q000502:physiology*; D006801:Humans; D020014:K562 Cells; D008969:Molecular Sequence Data; D011401:Promoter Regions, Genetic; D012045:Regulatory Sequences, Nucleic Acid; D014157:Transcription Factors / Q000235:genetics / Q000502:physiology; D024363:Transcription Initiation Site
chemical_list: D002843:Chromatin; D006657:Histones; D014157:Transcription Factors