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A gateway for phylogenetic analysis powered by grid computing featuring GARLI 2.0.
Bazinet, Adam L; Zwickl, Derrick J; Cummings, Michael P.
Afiliación
  • Bazinet AL; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742-3360, USA, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721-0088, USA adam.bazinet@umiacs.umd.edu.
  • Zwickl DJ; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742-3360, USA, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721-0088, USA.
  • Cummings MP; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742-3360, USA, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721-0088, USA.
Syst Biol ; 63(5): 812-8, 2014 Sep.
Article en En | MEDLINE | ID: mdl-24789072
ABSTRACT
We introduce molecularevolution.org, a publicly available gateway for high-throughput, maximum-likelihood phylogenetic analysis powered by grid computing. The gateway features a garli 2.0 web service that enables a user to quickly and easily submit thousands of maximum likelihood tree searches or bootstrap searches that are executed in parallel on distributed computing resources. The garli web service allows one to easily specify partitioned substitution models using a graphical interface, and it performs sophisticated post-processing of phylogenetic results. Although the garli web service has been used by the research community for over three years, here we formally announce the availability of the service, describe its capabilities, highlight new features and recent improvements, and provide details about how the grid system efficiently delivers high-quality phylogenetic results.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Filogenia / Programas Informáticos / Clasificación Idioma: En Revista: Syst Biol Asunto de la revista: BIOLOGIA Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Filogenia / Programas Informáticos / Clasificación Idioma: En Revista: Syst Biol Asunto de la revista: BIOLOGIA Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos