A MapReduce-based Algorithm for Motif Search

Abstract

Motif search plays an important role in gene finding and understanding gene regulation relationship. Motif search is one of the most challenging problems in bioinformatics. In this paper, we present three data partitions for the PMSP algorithm and propose the PMSP MapReduce algorithm (PMSPMR) for solving the motif search problem. For instances of the problem with different difficulties, the experimental results on the Hadoop cluster demonstrate that PMSPMR has good scalability. In particular, for the more difficult motif search problems, PMSPMR shows its advantage because the speedup is almost linearly proportional to the number of nodes in the Hadoop cluster. We also present experimental results on realistic biological data by identifying known transcriptional regulatory motifs in eukaryotes as well as in actual promoter sequences extracted from Saccharomyces cerevisiae.