hiHMM
:: DESCRIPTION
hiHMM (hierarchically-linked infinite hidden Markov model) is a new Bayesian non-parametric method to jointly infer chromatin state maps in multiple genomes (different cell types, developmental stages, even multiple species) using genome-wide histone modification data.
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::DEVELOPER
SNUBI (Snubi’s Not Unics, Biomedical Informatics.)
:: SCREENSHOTS
N/A
:: REQUIREMENTS
- Windows/ Linux
- MatLab/ R
:: DOWNLOAD
:: MORE INFORMATION
Citation:
hiHMM: Bayesian non-parametric joint inference of chromatin state maps.
Sohn KA, Ho JW, Djordjevic D, Jeong HH, Park PJ, Kim JH.
Bioinformatics. 2015 Feb 27. pii: btv117.