@article{hoffman:unsupervised,
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/.},
author = {Hoffman, Michael M and Buske, Orion J and Wang, Jie and Weng, Zhiping and Bilmes, Jeff A and Noble, William Stafford},
doi = {10.1038/nmeth.1937},
journal = {Nature Methods},
keywords = {Segway,chromatin,functional genomics,segmentation},
title = {{Unsupervised pattern discovery in human chromatin structure through genomic segmentation}},
url = {http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.1937.html},
volume = {In press},
year = {2012}
}