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- Title
Unsupervised pattern discovery in human chromatin structure through genomic segmentation.
- Authors
Hoffman, Michael M; Buske, Orion J; Wang, Jie; Weng, Zhiping; Bilmes, Jeff A; Noble, William Stafford
- 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/.
- Publication
Nature methods, 2012, Vol 9, Issue 5, p473
- ISSN
1548-7105
- Publication type
Journal Article
- DOI
10.1038/nmeth.1937