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BioMed Research International
Volume 2017, Article ID 6274513, 12 pages
https://doi.org/10.1155/2017/6274513
Research Article

A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model

School of Computer Science and Technology, Xidian University, Xi’an, Shaanxi, China

Correspondence should be addressed to Hongwei Huo; nc.ude.naidix.liam@ouhwh

Received 23 October 2016; Revised 6 March 2017; Accepted 23 March 2017; Published 11 April 2017

Academic Editor: Hesham H. Ali

Copyright © 2017 Haitao Guo and Hongwei Huo. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The discovery of cis-regulatory modules (CRMs) is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them.