Unknown

Dataset Information

0

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/.

SUBMITTER: Hoffman MM 

PROVIDER: S-EPMC3340533 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

altmetric image

Publications

Unsupervised pattern discovery in human chromatin structure through genomic segmentation.

Hoffman Michael M MM   Buske Orion J OJ   Wang Jie J   Weng Zhiping Z   Bilmes Jeff A JA   Noble William Stafford WS  

Nature methods 20120318 5


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 ht  ...[more]

Similar Datasets

| S-EPMC11319202 | biostudies-literature
| S-EPMC7054322 | biostudies-literature
| S-EPMC4769136 | biostudies-literature
| S-EPMC8662848 | biostudies-literature
| S-EPMC3300000 | biostudies-literature
| S-EPMC3135579 | biostudies-literature
| S-EPMC5708642 | biostudies-literature
| S-EPMC3600490 | biostudies-literature
| S-EPMC3431495 | biostudies-literature
| S-EPMC10168505 | biostudies-literature