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MEME-LaB: motif analysis in clusters
Summary: Genome-wide expression analysis can result in large numbers of clusters of co-expressed genes. Although there are tools for ab initio discovery of transcription factor-binding sites, most do not provide a quick and easy way to study large numbers of clusters. To address this, we introduce a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694638/ https://www.ncbi.nlm.nih.gov/pubmed/23681125 http://dx.doi.org/10.1093/bioinformatics/btt248 |
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author | Brown, Paul Baxter, Laura Hickman, Richard Beynon, Jim Moore, Jonathan D. Ott, Sascha |
author_facet | Brown, Paul Baxter, Laura Hickman, Richard Beynon, Jim Moore, Jonathan D. Ott, Sascha |
author_sort | Brown, Paul |
collection | PubMed |
description | Summary: Genome-wide expression analysis can result in large numbers of clusters of co-expressed genes. Although there are tools for ab initio discovery of transcription factor-binding sites, most do not provide a quick and easy way to study large numbers of clusters. To address this, we introduce a web tool called MEME-LaB. The tool wraps MEME (an ab initio motif finder), providing an interface for users to input multiple gene clusters, retrieve promoter sequences, run motif finding and then easily browse and condense the results, facilitating better interpretation of the results from large-scale datasets. Availability: MEME-LaB is freely accessible at: http://wsbc.warwick.ac.uk/wsbcToolsWebpage/. Contact: p.e.brown@warwick.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-3694638 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-36946382013-06-27 MEME-LaB: motif analysis in clusters Brown, Paul Baxter, Laura Hickman, Richard Beynon, Jim Moore, Jonathan D. Ott, Sascha Bioinformatics Applications Notes Summary: Genome-wide expression analysis can result in large numbers of clusters of co-expressed genes. Although there are tools for ab initio discovery of transcription factor-binding sites, most do not provide a quick and easy way to study large numbers of clusters. To address this, we introduce a web tool called MEME-LaB. The tool wraps MEME (an ab initio motif finder), providing an interface for users to input multiple gene clusters, retrieve promoter sequences, run motif finding and then easily browse and condense the results, facilitating better interpretation of the results from large-scale datasets. Availability: MEME-LaB is freely accessible at: http://wsbc.warwick.ac.uk/wsbcToolsWebpage/. Contact: p.e.brown@warwick.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2013-07-01 2013-05-14 /pmc/articles/PMC3694638/ /pubmed/23681125 http://dx.doi.org/10.1093/bioinformatics/btt248 Text en © The Author 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Brown, Paul Baxter, Laura Hickman, Richard Beynon, Jim Moore, Jonathan D. Ott, Sascha MEME-LaB: motif analysis in clusters |
title | MEME-LaB: motif analysis in clusters |
title_full | MEME-LaB: motif analysis in clusters |
title_fullStr | MEME-LaB: motif analysis in clusters |
title_full_unstemmed | MEME-LaB: motif analysis in clusters |
title_short | MEME-LaB: motif analysis in clusters |
title_sort | meme-lab: motif analysis in clusters |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694638/ https://www.ncbi.nlm.nih.gov/pubmed/23681125 http://dx.doi.org/10.1093/bioinformatics/btt248 |
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