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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...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2004
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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. |
format | Text |
id | pubmed-449910 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2004 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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