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

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2017
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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.
Reference Key
guo2017abiomed Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Guo, Haitao;Huo, Hongwei;
Journal BioMed research international
Year 2017
DOI
DOI not found
URL
http://dx.doi.org/10.1155/2017/6274513
Keywords
Medicine Information technology economics as a science commercial geography. economic geography mathematics applied mathematics. quantitative methods Medicine

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