Repulsive parallel MCMC algorithm for discovering diverse motifs from large sequence sets.

ABSTRACT:

Motivation

The motif discovery problem consists of finding recurring patterns of short strings in a set of nucleotide sequences. This classical problem is receiving renewed attention as most early motif discovery methods lack the ability to handle large data of recent genome-wide ChIP studies. New ChIP-tailored methods focus on reducing computation time and pay little regard to the accuracy of motif detection. Unlike such methods, our method focuses on increasing the detection accuracy while maintaining the computation efficiency at an acceptable level. The major advantage of our method is that it can mine diverse multiple motifs undetectable by current methods.

Results

The repulsive parallel Markov chain Monte Carlo (RPMCMC) algorithm that we propose is a parallel version o

SUBMITTER: Ikebata H 

PROVIDER: S-EPMC4426842 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature