A Local Genetic Algorithm for the Identification of Condition-Specific MicroRNA-Gene Modules
Transcription factor and microRNA are two types of key regulators of gene expression. Their regulatory mechanisms are highly complex. In this study, we propose a computational method to predict condition-specific regulatory modules that consist of microRNAs, transcription factors, and their commonly...
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Wiley
2013-01-01
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Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2013/197406 |
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author | Wenbo Mu Damian Roqueiro Yang Dai |
author_facet | Wenbo Mu Damian Roqueiro Yang Dai |
author_sort | Wenbo Mu |
collection | DOAJ |
description | Transcription factor and microRNA are two types of key regulators of gene expression. Their regulatory mechanisms are highly complex. In this study, we propose a computational method to predict condition-specific regulatory modules that consist of microRNAs, transcription factors, and their commonly regulated genes. We used matched global expression profiles of mRNAs and microRNAs together with the predicted targets of transcription factors and microRNAs to construct an underlying regulatory network. Our method searches for highly scored modules from the network based on a two-step heuristic method that combines genetic and local search algorithms. Using two matched expression datasets, we demonstrate that our method can identify highly scored modules with statistical significance and biological relevance. The identified regulatory modules may provide useful insights on the mechanisms of transcription factors and microRNAs. |
format | Article |
id | doaj-art-786ebe7097654ab499933504cb9494f0 |
institution | Kabale University |
issn | 1537-744X |
language | English |
publishDate | 2013-01-01 |
publisher | Wiley |
record_format | Article |
series | The Scientific World Journal |
spelling | doaj-art-786ebe7097654ab499933504cb9494f02025-02-03T01:31:25ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/197406197406A Local Genetic Algorithm for the Identification of Condition-Specific MicroRNA-Gene ModulesWenbo Mu0Damian Roqueiro1Yang Dai2Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USADepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USADepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USATranscription factor and microRNA are two types of key regulators of gene expression. Their regulatory mechanisms are highly complex. In this study, we propose a computational method to predict condition-specific regulatory modules that consist of microRNAs, transcription factors, and their commonly regulated genes. We used matched global expression profiles of mRNAs and microRNAs together with the predicted targets of transcription factors and microRNAs to construct an underlying regulatory network. Our method searches for highly scored modules from the network based on a two-step heuristic method that combines genetic and local search algorithms. Using two matched expression datasets, we demonstrate that our method can identify highly scored modules with statistical significance and biological relevance. The identified regulatory modules may provide useful insights on the mechanisms of transcription factors and microRNAs.http://dx.doi.org/10.1155/2013/197406 |
spellingShingle | Wenbo Mu Damian Roqueiro Yang Dai A Local Genetic Algorithm for the Identification of Condition-Specific MicroRNA-Gene Modules The Scientific World Journal |
title | A Local Genetic Algorithm for the Identification of Condition-Specific MicroRNA-Gene Modules |
title_full | A Local Genetic Algorithm for the Identification of Condition-Specific MicroRNA-Gene Modules |
title_fullStr | A Local Genetic Algorithm for the Identification of Condition-Specific MicroRNA-Gene Modules |
title_full_unstemmed | A Local Genetic Algorithm for the Identification of Condition-Specific MicroRNA-Gene Modules |
title_short | A Local Genetic Algorithm for the Identification of Condition-Specific MicroRNA-Gene Modules |
title_sort | local genetic algorithm for the identification of condition specific microrna gene modules |
url | http://dx.doi.org/10.1155/2013/197406 |
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