The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
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/.
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Metadata
- Authors
- Hoffman, M. M., Buske, O. J., Wang, J., Weng, Z., Bilmes, J. A., & Noble, W. S.
- Venue
- Nature Methods
- Published
- 2012-03-18
- Volume
- 9
- Issue
- 5
- Pages
- 473-476
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W4230875896
- Cited by
- 565
- References
- 2
- FWCI
- 15.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
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