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Genomic Promoter Analysis Predicts Functional Transcription Factor Binding

Background. The computational identification of functional transcription factor binding sites (TFBSs) remains a major challenge of computational biology. Results. We have analyzed the conserved promoter sequences for the complete set of human RefSeq genes using our conserved transcription factor bin...

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Detalles Bibliográficos
Autores principales: Rao, J. Sunil, Karanam, Suresh, McCabe, Colleen D., Moreno, Carlos S.
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768302/
https://www.ncbi.nlm.nih.gov/pubmed/19865592
http://dx.doi.org/10.1155/2008/369830
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author Rao, J. Sunil
Karanam, Suresh
McCabe, Colleen D.
Moreno, Carlos S.
author_facet Rao, J. Sunil
Karanam, Suresh
McCabe, Colleen D.
Moreno, Carlos S.
author_sort Rao, J. Sunil
collection PubMed
description Background. The computational identification of functional transcription factor binding sites (TFBSs) remains a major challenge of computational biology. Results. We have analyzed the conserved promoter sequences for the complete set of human RefSeq genes using our conserved transcription factor binding site (CONFAC) software. CONFAC identified 16296 human-mouse ortholog gene pairs, and of those pairs, 9107 genes contained conserved TFBS in the 3 kb proximal promoter and first intron. To attempt to predict in vivo occupancy of transcription factor binding sites, we developed a novel marginal effect isolator algorithm that builds upon Bayesian methods for multigroup TFBS filtering and predicted the in vivo occupancy of two transcription factors with an overall accuracy of 84%. Conclusion. Our analyses show that integration of chromatin immunoprecipitation data with conserved TFBS analysis can be used to generate accurate predictions of functional TFBS. They also show that TFBS cooccurrence can be used to predict transcription factor binding to promoters in vivo.
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spelling pubmed-27683022009-10-27 Genomic Promoter Analysis Predicts Functional Transcription Factor Binding Rao, J. Sunil Karanam, Suresh McCabe, Colleen D. Moreno, Carlos S. Adv Bioinformatics Research Article Background. The computational identification of functional transcription factor binding sites (TFBSs) remains a major challenge of computational biology. Results. We have analyzed the conserved promoter sequences for the complete set of human RefSeq genes using our conserved transcription factor binding site (CONFAC) software. CONFAC identified 16296 human-mouse ortholog gene pairs, and of those pairs, 9107 genes contained conserved TFBS in the 3 kb proximal promoter and first intron. To attempt to predict in vivo occupancy of transcription factor binding sites, we developed a novel marginal effect isolator algorithm that builds upon Bayesian methods for multigroup TFBS filtering and predicted the in vivo occupancy of two transcription factors with an overall accuracy of 84%. Conclusion. Our analyses show that integration of chromatin immunoprecipitation data with conserved TFBS analysis can be used to generate accurate predictions of functional TFBS. They also show that TFBS cooccurrence can be used to predict transcription factor binding to promoters in vivo. Hindawi Publishing Corporation 2008 2008-10-30 /pmc/articles/PMC2768302/ /pubmed/19865592 http://dx.doi.org/10.1155/2008/369830 Text en Copyright © 2008 J. Sunil Rao 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
Rao, J. Sunil
Karanam, Suresh
McCabe, Colleen D.
Moreno, Carlos S.
Genomic Promoter Analysis Predicts Functional Transcription Factor Binding
title Genomic Promoter Analysis Predicts Functional Transcription Factor Binding
title_full Genomic Promoter Analysis Predicts Functional Transcription Factor Binding
title_fullStr Genomic Promoter Analysis Predicts Functional Transcription Factor Binding
title_full_unstemmed Genomic Promoter Analysis Predicts Functional Transcription Factor Binding
title_short Genomic Promoter Analysis Predicts Functional Transcription Factor Binding
title_sort genomic promoter analysis predicts functional transcription factor binding
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768302/
https://www.ncbi.nlm.nih.gov/pubmed/19865592
http://dx.doi.org/10.1155/2008/369830
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