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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...

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Detalles Bibliográficos
Autores principales: Brown, Paul, Baxter, Laura, Hickman, Richard, Beynon, Jim, Moore, Jonathan D., Ott, Sascha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
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.
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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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