hiHMM – Bayesian non-parametric joint inference of Chromatin State Maps

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

 hiHMM

:: 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.