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c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression

BACKGROUND: Computational methods for characterizing novel transcription factor binding sites search for sequence patterns or "motifs" that appear repeatedly in genomic regions of interest. Correlation-based motif finding strategies are used to identify motifs that correlate with expressio...

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Detalles Bibliográficos
Autores principales: Kechris, Katerina, Li, Hao
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2626603/
https://www.ncbi.nlm.nih.gov/pubmed/19040743
http://dx.doi.org/10.1186/1471-2105-9-506
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author Kechris, Katerina
Li, Hao
author_facet Kechris, Katerina
Li, Hao
author_sort Kechris, Katerina
collection PubMed
description BACKGROUND: Computational methods for characterizing novel transcription factor binding sites search for sequence patterns or "motifs" that appear repeatedly in genomic regions of interest. Correlation-based motif finding strategies are used to identify motifs that correlate with expression data and do not rely on promoter sequences from a pre-determined set of genes. RESULTS: In this work, we describe a method for predicting motifs that combines the correlation-based strategy with phylogenetic footprinting, where motifs are identified by evaluating orthologous sequence regions from multiple species. Our method, c-REDUCE, can account for variability at a motif position inferred from evolutionary information. c-REDUCE has been tested on ChIP-chip data for yeast transcription factors and on gene expression data in Drosophila. CONCLUSION: Our results indicate that utilizing sequence conservation information in addition to correlation-based methods improves the identification of known motifs.
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spelling pubmed-26266032009-01-15 c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression Kechris, Katerina Li, Hao BMC Bioinformatics Methodology Article BACKGROUND: Computational methods for characterizing novel transcription factor binding sites search for sequence patterns or "motifs" that appear repeatedly in genomic regions of interest. Correlation-based motif finding strategies are used to identify motifs that correlate with expression data and do not rely on promoter sequences from a pre-determined set of genes. RESULTS: In this work, we describe a method for predicting motifs that combines the correlation-based strategy with phylogenetic footprinting, where motifs are identified by evaluating orthologous sequence regions from multiple species. Our method, c-REDUCE, can account for variability at a motif position inferred from evolutionary information. c-REDUCE has been tested on ChIP-chip data for yeast transcription factors and on gene expression data in Drosophila. CONCLUSION: Our results indicate that utilizing sequence conservation information in addition to correlation-based methods improves the identification of known motifs. BioMed Central 2008-11-28 /pmc/articles/PMC2626603/ /pubmed/19040743 http://dx.doi.org/10.1186/1471-2105-9-506 Text en Copyright © 2008 Kechris and Li; 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 Methodology Article
Kechris, Katerina
Li, Hao
c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression
title c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression
title_full c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression
title_fullStr c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression
title_full_unstemmed c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression
title_short c-REDUCE: Incorporating sequence conservation to detect motifs that correlate with expression
title_sort c-reduce: incorporating sequence conservation to detect motifs that correlate with expression
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2626603/
https://www.ncbi.nlm.nih.gov/pubmed/19040743
http://dx.doi.org/10.1186/1471-2105-9-506
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