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...
| Main Authors: | , , , , , |
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| Format: | Online |
| Language: | English |
| Published: |
Oxford University Press
2015
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4481846/ |