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MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures

BACKGROUND: Motifs are regulatory elements that will activate or inhibit the expression of related genes when proteins (such as transcription factors, TFs) bind to them. Therefore, motif finding is important to understand the mechanisms of gene regulation. De novo discovery of regulatory elements, l...

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Autores principales: Zhang, Yizhe, He, Yupeng, Zheng, Guangyong, Wei, Chaochun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4474412/
https://www.ncbi.nlm.nih.gov/pubmed/26099518
http://dx.doi.org/10.1186/1471-2164-16-S7-S13
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author Zhang, Yizhe
He, Yupeng
Zheng, Guangyong
Wei, Chaochun
author_facet Zhang, Yizhe
He, Yupeng
Zheng, Guangyong
Wei, Chaochun
author_sort Zhang, Yizhe
collection PubMed
description BACKGROUND: Motifs are regulatory elements that will activate or inhibit the expression of related genes when proteins (such as transcription factors, TFs) bind to them. Therefore, motif finding is important to understand the mechanisms of gene regulation. De novo discovery of regulatory elements, like transcription factor binding sites (TFBSs), has long been a major challenge to gain insight on mechanisms of gene regulation. Recent advances in experimental profiling of genome-wide signals such as histone modifications and DNase I hypersensitivity sites allow scientists to develop better computational methods to enhance motif discovery. However, existing methods for motif finding suffer from high false positive rates and slow speed, and it's difficult to evaluate the performance of these methods systematically. RESULT: Here we present MOST+, a motif finder integrating genomic sequences and genome-wide signals such as intensity and shape features from histone modification marks and DNase I hypersensitivity sites, to improve the prediction accuracy. MOST+ can detect motifs from a large input sequence of about 100 Mbs within a few minutes. Systematic comparison method has been established and MOST+ has been compared with existing methods. CONCLUSION: MOST+ is a fast and accurate de novo method for motif finding by integrating genomic sequence and experimental signals as clues.
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spelling pubmed-44744122015-06-25 MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures Zhang, Yizhe He, Yupeng Zheng, Guangyong Wei, Chaochun BMC Genomics Research BACKGROUND: Motifs are regulatory elements that will activate or inhibit the expression of related genes when proteins (such as transcription factors, TFs) bind to them. Therefore, motif finding is important to understand the mechanisms of gene regulation. De novo discovery of regulatory elements, like transcription factor binding sites (TFBSs), has long been a major challenge to gain insight on mechanisms of gene regulation. Recent advances in experimental profiling of genome-wide signals such as histone modifications and DNase I hypersensitivity sites allow scientists to develop better computational methods to enhance motif discovery. However, existing methods for motif finding suffer from high false positive rates and slow speed, and it's difficult to evaluate the performance of these methods systematically. RESULT: Here we present MOST+, a motif finder integrating genomic sequences and genome-wide signals such as intensity and shape features from histone modification marks and DNase I hypersensitivity sites, to improve the prediction accuracy. MOST+ can detect motifs from a large input sequence of about 100 Mbs within a few minutes. Systematic comparison method has been established and MOST+ has been compared with existing methods. CONCLUSION: MOST+ is a fast and accurate de novo method for motif finding by integrating genomic sequence and experimental signals as clues. BioMed Central 2015-06-11 /pmc/articles/PMC4474412/ /pubmed/26099518 http://dx.doi.org/10.1186/1471-2164-16-S7-S13 Text en Copyright © 2015 Zhang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zhang, Yizhe
He, Yupeng
Zheng, Guangyong
Wei, Chaochun
MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures
title MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures
title_full MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures
title_fullStr MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures
title_full_unstemmed MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures
title_short MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures
title_sort most+: a de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4474412/
https://www.ncbi.nlm.nih.gov/pubmed/26099518
http://dx.doi.org/10.1186/1471-2164-16-S7-S13
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