Identification of microRNA-mRNA modules using microarray data

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are post-transcriptional regulators of mRNA expression and are involved in numerous cellular processes. Consequently, miRNAs are an important component of gene regulatory networks and an improved understanding of m...

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Main Authors: Lutherborrow Mark, Jayaswal Vivek, Ma David DF, Yang Yee H
Format: Article
Language:English
Published: BMC 2011-03-01
Series:BMC Genomics
Online Access:http://www.biomedcentral.com/1471-2164/12/138
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spelling doaj-2de8914742ee4690a3e8491b2c79df592020-11-25T02:09:17ZengBMCBMC Genomics1471-21642011-03-0112113810.1186/1471-2164-12-138Identification of microRNA-mRNA modules using microarray dataLutherborrow MarkJayaswal VivekMa David DFYang Yee H<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are post-transcriptional regulators of mRNA expression and are involved in numerous cellular processes. Consequently, miRNAs are an important component of gene regulatory networks and an improved understanding of miRNAs will further our knowledge of these networks. There is a many-to-many relationship between miRNAs and mRNAs because a single miRNA targets multiple mRNAs and a single mRNA is targeted by multiple miRNAs. However, most of the current methods for the identification of regulatory miRNAs and their target mRNAs ignore this biological observation and focus on miRNA-mRNA pairs.</p> <p>Results</p> <p>We propose a two-step method for the identification of many-to-many relationships between miRNAs and mRNAs. In the first step, we obtain miRNA and mRNA clusters using a combination of miRNA-target mRNA prediction algorithms and microarray expression data. In the second step, we determine the associations between miRNA clusters and mRNA clusters based on changes in miRNA and mRNA expression profiles. We consider the miRNA-mRNA clusters with statistically significant associations to be potentially regulatory and, therefore, of biological interest.</p> <p>Conclusions</p> <p>Our method reduces the interactions between several hundred miRNAs and several thousand mRNAs to a few miRNA-mRNA groups, thereby facilitating a more meaningful biological analysis and a more targeted experimental validation.</p> http://www.biomedcentral.com/1471-2164/12/138
collection DOAJ
language English
format Article
sources DOAJ
author Lutherborrow Mark
Jayaswal Vivek
Ma David DF
Yang Yee H
spellingShingle Lutherborrow Mark
Jayaswal Vivek
Ma David DF
Yang Yee H
Identification of microRNA-mRNA modules using microarray data
BMC Genomics
author_facet Lutherborrow Mark
Jayaswal Vivek
Ma David DF
Yang Yee H
author_sort Lutherborrow Mark
title Identification of microRNA-mRNA modules using microarray data
title_short Identification of microRNA-mRNA modules using microarray data
title_full Identification of microRNA-mRNA modules using microarray data
title_fullStr Identification of microRNA-mRNA modules using microarray data
title_full_unstemmed Identification of microRNA-mRNA modules using microarray data
title_sort identification of microrna-mrna modules using microarray data
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2011-03-01
description <p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are post-transcriptional regulators of mRNA expression and are involved in numerous cellular processes. Consequently, miRNAs are an important component of gene regulatory networks and an improved understanding of miRNAs will further our knowledge of these networks. There is a many-to-many relationship between miRNAs and mRNAs because a single miRNA targets multiple mRNAs and a single mRNA is targeted by multiple miRNAs. However, most of the current methods for the identification of regulatory miRNAs and their target mRNAs ignore this biological observation and focus on miRNA-mRNA pairs.</p> <p>Results</p> <p>We propose a two-step method for the identification of many-to-many relationships between miRNAs and mRNAs. In the first step, we obtain miRNA and mRNA clusters using a combination of miRNA-target mRNA prediction algorithms and microarray expression data. In the second step, we determine the associations between miRNA clusters and mRNA clusters based on changes in miRNA and mRNA expression profiles. We consider the miRNA-mRNA clusters with statistically significant associations to be potentially regulatory and, therefore, of biological interest.</p> <p>Conclusions</p> <p>Our method reduces the interactions between several hundred miRNAs and several thousand mRNAs to a few miRNA-mRNA groups, thereby facilitating a more meaningful biological analysis and a more targeted experimental validation.</p>
url http://www.biomedcentral.com/1471-2164/12/138
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