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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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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. |
format | Online Article Text |
id | pubmed-4132326 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
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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