• Unsupervised pattern discovery in human chromatin structure through genomic segmentation

      Hoffman, Michael M.; Buske, Orion J.; Wang, Jie; Weng, Zhiping; Bilmes, Jeff A.; Noble, William Stafford (2012-03-18)
      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/.