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Predicting transcription factor binding sites using local over-representation and comparative genomics

BACKGROUND: Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs) in coexpressed or coregulated genes. However, this is a challenging problem, espec...

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Detalles Bibliográficos
Autores principales: Defrance, Matthieu, Touzet, Hélène
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1570149/
https://www.ncbi.nlm.nih.gov/pubmed/16945132
http://dx.doi.org/10.1186/1471-2105-7-396
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author Defrance, Matthieu
Touzet, Hélène
author_facet Defrance, Matthieu
Touzet, Hélène
author_sort Defrance, Matthieu
collection PubMed
description BACKGROUND: Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs) in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering higher eukaryotic organisms. RESULTS: We have developed a method, named TFM-Explorer, that searches for locally overrepresented TFBSs in a set of coregulated genes, which are modeled by profiles provided by a database of position weight matrices. The novelty of the method is that it takes advantage of spatial conservation in the sequence and supports multiple species. The efficiency of the underlying algorithm and its robustness to noise allow weak regulatory signals to be detected in large heterogeneous data sets. CONCLUSION: TFM-Explorer provides an efficient way to predict TFBS overrepresentation in related sequences. Promising results were obtained in a variety of examples in human, mouse, and rat genomes. The software is publicly available at .
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spelling pubmed-15701492006-09-26 Predicting transcription factor binding sites using local over-representation and comparative genomics Defrance, Matthieu Touzet, Hélène BMC Bioinformatics Software BACKGROUND: Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs) in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering higher eukaryotic organisms. RESULTS: We have developed a method, named TFM-Explorer, that searches for locally overrepresented TFBSs in a set of coregulated genes, which are modeled by profiles provided by a database of position weight matrices. The novelty of the method is that it takes advantage of spatial conservation in the sequence and supports multiple species. The efficiency of the underlying algorithm and its robustness to noise allow weak regulatory signals to be detected in large heterogeneous data sets. CONCLUSION: TFM-Explorer provides an efficient way to predict TFBS overrepresentation in related sequences. Promising results were obtained in a variety of examples in human, mouse, and rat genomes. The software is publicly available at . BioMed Central 2006-08-31 /pmc/articles/PMC1570149/ /pubmed/16945132 http://dx.doi.org/10.1186/1471-2105-7-396 Text en Copyright © 2006 Defrance and Touzet; 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
Defrance, Matthieu
Touzet, Hélène
Predicting transcription factor binding sites using local over-representation and comparative genomics
title Predicting transcription factor binding sites using local over-representation and comparative genomics
title_full Predicting transcription factor binding sites using local over-representation and comparative genomics
title_fullStr Predicting transcription factor binding sites using local over-representation and comparative genomics
title_full_unstemmed Predicting transcription factor binding sites using local over-representation and comparative genomics
title_short Predicting transcription factor binding sites using local over-representation and comparative genomics
title_sort predicting transcription factor binding sites using local over-representation and comparative genomics
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1570149/
https://www.ncbi.nlm.nih.gov/pubmed/16945132
http://dx.doi.org/10.1186/1471-2105-7-396
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