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hiHMM: Bayesian non-parametric joint inference of chromatin state maps
Motivation: Genome-wide mapping of chromatin states is essential for defining regulatory elements and inferring their activities in eukaryotic genomes. A number of hidden Markov model (HMM)-based methods have been developed to infer chromatin state maps from genome-wide histone modification data for...
Autores principales: | Sohn, Kyung-Ah, Ho, Joshua W. K., Djordjevic, Djordje, Jeong, Hyun-hwan, Park, Peter J., Kim, Ju Han |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481846/ https://www.ncbi.nlm.nih.gov/pubmed/25725496 http://dx.doi.org/10.1093/bioinformatics/btv117 |
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