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

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 p...

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Detalles Bibliográficos
Autores principales: Guo, Haitao, Huo, Hongwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5405574/
https://www.ncbi.nlm.nih.gov/pubmed/28497059
http://dx.doi.org/10.1155/2017/6274513
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author Guo, Haitao
Huo, Hongwei
author_facet Guo, Haitao
Huo, Hongwei
author_sort Guo, Haitao
collection PubMed
description 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.
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spelling pubmed-54055742017-05-11 A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model Guo, Haitao Huo, Hongwei Biomed Res Int Research Article 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. Hindawi 2017 2017-04-11 /pmc/articles/PMC5405574/ /pubmed/28497059 http://dx.doi.org/10.1155/2017/6274513 Text en Copyright © 2017 Haitao Guo and Hongwei Huo. https://creativecommons.org/licenses/by/4.0/ 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.
spellingShingle Research Article
Guo, Haitao
Huo, Hongwei
A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model
title A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model
title_full A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model
title_fullStr A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model
title_full_unstemmed A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model
title_short A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model
title_sort new algorithm for identifying cis-regulatory modules based on hidden markov model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5405574/
https://www.ncbi.nlm.nih.gov/pubmed/28497059
http://dx.doi.org/10.1155/2017/6274513
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