Cargando…

XcisClique: analysis of regulatory bicliques

BACKGROUND: Modeling of cis-elements or regulatory motifs in promoter (upstream) regions of genes is a challenging computational problem. In this work, set of regulatory motifs simultaneously present in the promoters of a set of genes is modeled as a biclique in a suitably defined bipartite graph. A...

Descripción completa

Detalles Bibliográficos
Autores principales: Pati, Amrita, Vasquez-Robinet, Cecilia, Heath, Lenwood S, Grene, Ruth, Murali, TM
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1513260/
https://www.ncbi.nlm.nih.gov/pubmed/16630346
http://dx.doi.org/10.1186/1471-2105-7-218
_version_ 1782128470373957632
author Pati, Amrita
Vasquez-Robinet, Cecilia
Heath, Lenwood S
Grene, Ruth
Murali, TM
author_facet Pati, Amrita
Vasquez-Robinet, Cecilia
Heath, Lenwood S
Grene, Ruth
Murali, TM
author_sort Pati, Amrita
collection PubMed
description BACKGROUND: Modeling of cis-elements or regulatory motifs in promoter (upstream) regions of genes is a challenging computational problem. In this work, set of regulatory motifs simultaneously present in the promoters of a set of genes is modeled as a biclique in a suitably defined bipartite graph. A biologically meaningful co-occurrence of multiple cis-elements in a gene promoter is assessed by the combined analysis of genomic and gene expression data. Greater statistical significance is associated with a set of genes that shares a common set of regulatory motifs, while simultaneously exhibiting highly correlated gene expression under given experimental conditions. METHODS: XcisClique, the system developed in this work, is a comprehensive infrastructure that associates annotated genome and gene expression data, models known cis-elements as regular expressions, identifies maximal bicliques in a bipartite gene-motif graph; and ranks bicliques based on their computed statistical significance. Significance is a function of the probability of occurrence of those motifs in a biclique (a hypergeometric distribution), and on the new sum of absolute values statistic (SAV) that uses Spearman correlations of gene expression vectors. SAV is a statistic well-suited for this purpose as described in the discussion. RESULTS: XcisClique identifies new motif and gene combinations that might indicate as yet unidentified involvement of sets of genes in biological functions and processes. It currently supports Arabidopsis thaliana and can be adapted to other organisms, assuming the existence of annotated genomic sequences, suitable gene expression data, and identified regulatory motifs. A subset of Xcis Clique functionalities, including the motif visualization component MotifSee, source code, and supplementary material are available at .
format Text
id pubmed-1513260
institution National Center for Biotechnology Information
language English
publishDate 2006
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-15132602006-07-20 XcisClique: analysis of regulatory bicliques Pati, Amrita Vasquez-Robinet, Cecilia Heath, Lenwood S Grene, Ruth Murali, TM BMC Bioinformatics Software BACKGROUND: Modeling of cis-elements or regulatory motifs in promoter (upstream) regions of genes is a challenging computational problem. In this work, set of regulatory motifs simultaneously present in the promoters of a set of genes is modeled as a biclique in a suitably defined bipartite graph. A biologically meaningful co-occurrence of multiple cis-elements in a gene promoter is assessed by the combined analysis of genomic and gene expression data. Greater statistical significance is associated with a set of genes that shares a common set of regulatory motifs, while simultaneously exhibiting highly correlated gene expression under given experimental conditions. METHODS: XcisClique, the system developed in this work, is a comprehensive infrastructure that associates annotated genome and gene expression data, models known cis-elements as regular expressions, identifies maximal bicliques in a bipartite gene-motif graph; and ranks bicliques based on their computed statistical significance. Significance is a function of the probability of occurrence of those motifs in a biclique (a hypergeometric distribution), and on the new sum of absolute values statistic (SAV) that uses Spearman correlations of gene expression vectors. SAV is a statistic well-suited for this purpose as described in the discussion. RESULTS: XcisClique identifies new motif and gene combinations that might indicate as yet unidentified involvement of sets of genes in biological functions and processes. It currently supports Arabidopsis thaliana and can be adapted to other organisms, assuming the existence of annotated genomic sequences, suitable gene expression data, and identified regulatory motifs. A subset of Xcis Clique functionalities, including the motif visualization component MotifSee, source code, and supplementary material are available at . BioMed Central 2006-04-21 /pmc/articles/PMC1513260/ /pubmed/16630346 http://dx.doi.org/10.1186/1471-2105-7-218 Text en Copyright © 2006 Pati et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Pati, Amrita
Vasquez-Robinet, Cecilia
Heath, Lenwood S
Grene, Ruth
Murali, TM
XcisClique: analysis of regulatory bicliques
title XcisClique: analysis of regulatory bicliques
title_full XcisClique: analysis of regulatory bicliques
title_fullStr XcisClique: analysis of regulatory bicliques
title_full_unstemmed XcisClique: analysis of regulatory bicliques
title_short XcisClique: analysis of regulatory bicliques
title_sort xcisclique: analysis of regulatory bicliques
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1513260/
https://www.ncbi.nlm.nih.gov/pubmed/16630346
http://dx.doi.org/10.1186/1471-2105-7-218
work_keys_str_mv AT patiamrita xciscliqueanalysisofregulatorybicliques
AT vasquezrobinetcecilia xciscliqueanalysisofregulatorybicliques
AT heathlenwoods xciscliqueanalysisofregulatorybicliques
AT greneruth xciscliqueanalysisofregulatorybicliques
AT muralitm xciscliqueanalysisofregulatorybicliques