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ViCTree: an automated framework for taxonomic classification from protein sequences.
Modha, Sejal; Thanki, Anil S; Cotmore, Susan F; Davison, Andrew J; Hughes, Joseph.
Afiliación
  • Modha S; MRC-University of Glasgow Centre for Virus Research, Glasgow, UK.
  • Thanki AS; Earlham Institute, Norwich Research Park, Norwich, UK.
  • Cotmore SF; Yale University Medical School, New Haven, CT, USA.
  • Davison AJ; MRC-University of Glasgow Centre for Virus Research, Glasgow, UK.
  • Hughes J; MRC-University of Glasgow Centre for Virus Research, Glasgow, UK.
Bioinformatics ; 34(13): 2195-2200, 2018 07 01.
Article en En | MEDLINE | ID: mdl-29474519
Motivation: The increasing rate of submission of genetic sequences into public databases is providing a growing resource for classifying the organisms that these sequences represent. To aid viral classification, we have developed ViCTree, which automatically integrates the relevant sets of sequences in NCBI GenBank and transforms them into an interactive maximum likelihood phylogenetic tree that can be updated automatically. ViCTree incorporates ViCTreeView, which is a JavaScript-based visualization tool that enables the tree to be explored interactively in the context of pairwise distance data. Results: To demonstrate utility, ViCTree was applied to subfamily Densovirinae of family Parvoviridae. This led to the identification of six new species of insect virus. Availability and implementation: ViCTree is open-source and can be run on any Linux- or Unix-based computer or cluster. A tutorial, the documentation and the source code are available under a GPL3 license, and can be accessed at http://bioinformatics.cvr.ac.uk/victree_web/. Supplementary information: Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Filogenia / Proteínas Virales / Virus / Programas Informáticos / Análisis de Secuencia de Proteína Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2018 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Filogenia / Proteínas Virales / Virus / Programas Informáticos / Análisis de Secuencia de Proteína Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2018 Tipo del documento: Article Pais de publicación: Reino Unido