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

• Published in: BioMed research international Vol. 2017; no. 2017; pp. 1 - 12
• Main Authors: Guo, Haitao, Huo, Hongwei
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2017; Hindawi; John Wiley & Sons, Inc
• Subjects: Algorithms; Analysis; DNA sequencing; Gene expression; Genetic regulation; Identification; Markov Chains; Markov processes; Methods; Nucleotide sequencing; Regulatory Elements, Transcriptional; Sequence Analysis, DNA - methods; Transcription factors; Transcription, Genetic
• ISSN: 2314-6133; 2314-6141; 2314-6141
• DOI: 10.1155/2017/6274513

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.