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Studying the Complex Expression Dependences between Sets of Coexpressed Genes

Organisms simplify the orchestration of gene expression by coregulating genes whose products function together in the cell. The use of clustering methods to obtain sets of coexpressed genes from expression arrays is very common; nevertheless there are no appropriate tools to study the expression net...

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Detalles Bibliográficos
Autores principales: Huerta, Mario, Casanova, Oriol, Barchino, Roberto, Flores, Jose, Querol, Enrique, Cedano, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4132326/
https://www.ncbi.nlm.nih.gov/pubmed/25147825
http://dx.doi.org/10.1155/2014/940821
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author Huerta, Mario
Casanova, Oriol
Barchino, Roberto
Flores, Jose
Querol, Enrique
Cedano, Juan
author_facet Huerta, Mario
Casanova, Oriol
Barchino, Roberto
Flores, Jose
Querol, Enrique
Cedano, Juan
author_sort Huerta, Mario
collection PubMed
description Organisms simplify the orchestration of gene expression by coregulating genes whose products function together in the cell. The use of clustering methods to obtain sets of coexpressed genes from expression arrays is very common; nevertheless there are no appropriate tools to study the expression networks among these sets of coexpressed genes. The aim of the developed tools is to allow studying the complex expression dependences that exist between sets of coexpressed genes. For this purpose, we start detecting the nonlinear expression relationships between pairs of genes, plus the coexpressed genes. Next, we form networks among sets of coexpressed genes that maintain nonlinear expression dependences between all of them. The expression relationship between the sets of coexpressed genes is defined by the expression relationship between the skeletons of these sets, where this skeleton represents the coexpressed genes with a well-defined nonlinear expression relationship with the skeleton of the other sets. As a result, we can study the nonlinear expression relationships between a target gene and other sets of coexpressed genes, or start the study from the skeleton of the sets, to study the complex relationships of activation and deactivation between the sets of coexpressed genes that carry out the different cellular processes present in the expression experiments.
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spelling pubmed-41323262014-08-21 Studying the Complex Expression Dependences between Sets of Coexpressed Genes Huerta, Mario Casanova, Oriol Barchino, Roberto Flores, Jose Querol, Enrique Cedano, Juan Biomed Res Int Research Article Organisms simplify the orchestration of gene expression by coregulating genes whose products function together in the cell. The use of clustering methods to obtain sets of coexpressed genes from expression arrays is very common; nevertheless there are no appropriate tools to study the expression networks among these sets of coexpressed genes. The aim of the developed tools is to allow studying the complex expression dependences that exist between sets of coexpressed genes. For this purpose, we start detecting the nonlinear expression relationships between pairs of genes, plus the coexpressed genes. Next, we form networks among sets of coexpressed genes that maintain nonlinear expression dependences between all of them. The expression relationship between the sets of coexpressed genes is defined by the expression relationship between the skeletons of these sets, where this skeleton represents the coexpressed genes with a well-defined nonlinear expression relationship with the skeleton of the other sets. As a result, we can study the nonlinear expression relationships between a target gene and other sets of coexpressed genes, or start the study from the skeleton of the sets, to study the complex relationships of activation and deactivation between the sets of coexpressed genes that carry out the different cellular processes present in the expression experiments. Hindawi Publishing Corporation 2014 2014-07-24 /pmc/articles/PMC4132326/ /pubmed/25147825 http://dx.doi.org/10.1155/2014/940821 Text en Copyright © 2014 Mario Huerta et al. https://creativecommons.org/licenses/by/3.0/ 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
Huerta, Mario
Casanova, Oriol
Barchino, Roberto
Flores, Jose
Querol, Enrique
Cedano, Juan
Studying the Complex Expression Dependences between Sets of Coexpressed Genes
title Studying the Complex Expression Dependences between Sets of Coexpressed Genes
title_full Studying the Complex Expression Dependences between Sets of Coexpressed Genes
title_fullStr Studying the Complex Expression Dependences between Sets of Coexpressed Genes
title_full_unstemmed Studying the Complex Expression Dependences between Sets of Coexpressed Genes
title_short Studying the Complex Expression Dependences between Sets of Coexpressed Genes
title_sort studying the complex expression dependences between sets of coexpressed genes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4132326/
https://www.ncbi.nlm.nih.gov/pubmed/25147825
http://dx.doi.org/10.1155/2014/940821
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