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Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrep-resented upstream motifs

BACKGROUND: Transcriptional regulation is a key mechanism in the functioning of the cell, and is mostly effected through transcription factors binding to specific recognition motifs located upstream of the coding region of the regulated gene. The computational identification of such motifs is made e...

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Autores principales: Corà, Davide, Di Cunto, Ferdinando, Provero, Paolo, Silengo, Lorenzo, Caselle, Michele
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2004
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC449910/
https://www.ncbi.nlm.nih.gov/pubmed/15137914
http://dx.doi.org/10.1186/1471-2105-5-57
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author Corà, Davide
Di Cunto, Ferdinando
Provero, Paolo
Silengo, Lorenzo
Caselle, Michele
author_facet Corà, Davide
Di Cunto, Ferdinando
Provero, Paolo
Silengo, Lorenzo
Caselle, Michele
author_sort Corà, Davide
collection PubMed
description BACKGROUND: Transcriptional regulation is a key mechanism in the functioning of the cell, and is mostly effected through transcription factors binding to specific recognition motifs located upstream of the coding region of the regulated gene. The computational identification of such motifs is made easier by the fact that they often appear several times in the upstream region of the regulated genes, so that the number of occurrences of relevant motifs is often significantly larger than expected by pure chance. RESULTS: To exploit this fact, we construct sets of genes characterized by the statistical overrepresentation of a certain motif in their upstream regions. Then we study the functional characterization of these sets by analyzing their annotation to Gene Ontology terms. For the sets showing a statistically significant specific functional characterization, we conjecture that the upstream motif characterizing the set is a binding site for a transcription factor involved in the regulation of the genes in the set. CONCLUSIONS: The method we propose is able to identify many known binding sites in S. cerevisiae and new candidate targets of regulation by known transcritpion factors. Its application to less well studied organisms is likely to be valuable in the exploration of their regulatory interaction network.
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spelling pubmed-4499102004-07-10 Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrep-resented upstream motifs Corà, Davide Di Cunto, Ferdinando Provero, Paolo Silengo, Lorenzo Caselle, Michele BMC Bioinformatics Research Article BACKGROUND: Transcriptional regulation is a key mechanism in the functioning of the cell, and is mostly effected through transcription factors binding to specific recognition motifs located upstream of the coding region of the regulated gene. The computational identification of such motifs is made easier by the fact that they often appear several times in the upstream region of the regulated genes, so that the number of occurrences of relevant motifs is often significantly larger than expected by pure chance. RESULTS: To exploit this fact, we construct sets of genes characterized by the statistical overrepresentation of a certain motif in their upstream regions. Then we study the functional characterization of these sets by analyzing their annotation to Gene Ontology terms. For the sets showing a statistically significant specific functional characterization, we conjecture that the upstream motif characterizing the set is a binding site for a transcription factor involved in the regulation of the genes in the set. CONCLUSIONS: The method we propose is able to identify many known binding sites in S. cerevisiae and new candidate targets of regulation by known transcritpion factors. Its application to less well studied organisms is likely to be valuable in the exploration of their regulatory interaction network. BioMed Central 2004-05-11 /pmc/articles/PMC449910/ /pubmed/15137914 http://dx.doi.org/10.1186/1471-2105-5-57 Text en Copyright © 2004 Corà et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
spellingShingle Research Article
Corà, Davide
Di Cunto, Ferdinando
Provero, Paolo
Silengo, Lorenzo
Caselle, Michele
Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrep-resented upstream motifs
title Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrep-resented upstream motifs
title_full Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrep-resented upstream motifs
title_fullStr Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrep-resented upstream motifs
title_full_unstemmed Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrep-resented upstream motifs
title_short Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrep-resented upstream motifs
title_sort computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrep-resented upstream motifs
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC449910/
https://www.ncbi.nlm.nih.gov/pubmed/15137914
http://dx.doi.org/10.1186/1471-2105-5-57
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