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DupliPHY-Web: a web server for DupliPHY and DupliPHY-ML
Summary: Gene duplication and loss are important processes in the evolution of gene families. Moreover, growth of families by duplication and retention is an important mechanism by which organisms gain new functions. Therefore the ability to infer the evolutionary histories of families is an importa...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4308661/ https://www.ncbi.nlm.nih.gov/pubmed/25294920 http://dx.doi.org/10.1093/bioinformatics/btu645 |
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author | Ames, Ryan M. Lovell, Simon C. |
author_facet | Ames, Ryan M. Lovell, Simon C. |
author_sort | Ames, Ryan M. |
collection | PubMed |
description | Summary: Gene duplication and loss are important processes in the evolution of gene families. Moreover, growth of families by duplication and retention is an important mechanism by which organisms gain new functions. Therefore the ability to infer the evolutionary histories of families is an important step in understanding the evolution of function. We have recently developed DupliPHY, a software tool to infer gene family histories using parsimony and maximum likelihood. Here, we present DupliPHY-Web a web server for DupliPHY that implements additional maximum likelihood functionality and provides users an intuitive interface to run DupliPHY. Availability and implementation: DupliPHY-Web is available at www.bioinf.manchester.ac.uk/dupliphy/ Contact: ryan.ames@manchester.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4308661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-43086612015-02-24 DupliPHY-Web: a web server for DupliPHY and DupliPHY-ML Ames, Ryan M. Lovell, Simon C. Bioinformatics Applications Notes Summary: Gene duplication and loss are important processes in the evolution of gene families. Moreover, growth of families by duplication and retention is an important mechanism by which organisms gain new functions. Therefore the ability to infer the evolutionary histories of families is an important step in understanding the evolution of function. We have recently developed DupliPHY, a software tool to infer gene family histories using parsimony and maximum likelihood. Here, we present DupliPHY-Web a web server for DupliPHY that implements additional maximum likelihood functionality and provides users an intuitive interface to run DupliPHY. Availability and implementation: DupliPHY-Web is available at www.bioinf.manchester.ac.uk/dupliphy/ Contact: ryan.ames@manchester.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2015-02-01 2014-10-07 /pmc/articles/PMC4308661/ /pubmed/25294920 http://dx.doi.org/10.1093/bioinformatics/btu645 Text en © The Author 2014. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Ames, Ryan M. Lovell, Simon C. DupliPHY-Web: a web server for DupliPHY and DupliPHY-ML |
title | DupliPHY-Web: a web server for DupliPHY and DupliPHY-ML |
title_full | DupliPHY-Web: a web server for DupliPHY and DupliPHY-ML |
title_fullStr | DupliPHY-Web: a web server for DupliPHY and DupliPHY-ML |
title_full_unstemmed | DupliPHY-Web: a web server for DupliPHY and DupliPHY-ML |
title_short | DupliPHY-Web: a web server for DupliPHY and DupliPHY-ML |
title_sort | dupliphy-web: a web server for dupliphy and dupliphy-ml |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4308661/ https://www.ncbi.nlm.nih.gov/pubmed/25294920 http://dx.doi.org/10.1093/bioinformatics/btu645 |
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