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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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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. |
format | Online Article Text |
id | pubmed-4474412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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