ViCTree: an automated framework for taxonomic classification from protein sequences | Zendy

Sejal Modha | Zendy; Anil S. Thanki | Zendy; Susan F. Cotmore | Zendy; Andrew J. Davison | Zendy; Joseph Hughes | Zendy

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ViCTree: an automated framework for taxonomic classification from protein sequences

Author(s) -

Sejal Modha,

Anil S. Thanki,

Susan F. Cotmore,

Andrew J. Davison,

Joseph Hughes

Publication year - 2018

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bty099

Subject(s) - computer science , unix , source code , context (archaeology) , genbank , javascript , perl , identification (biology) , phylogenetic tree , tree (set theory) , documentation , open source , java , programming language , software , biology , paleontology , mathematical analysis , biochemistry , botany , mathematics , gene

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.

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