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RocaSec: A standalone GUI-based package for robust co-evolutionary analysis of proteins.
Bioinformatics ; 2019 Dec 04.
Artigo em Inglês | MEDLINE | ID: mdl-31800008
ABSTRACT

SUMMARY:

Patterns of mutational correlations, learnt from protein sequences, have been shown to be informative of co-evolutionary sectors that are tightly linked to functional and/or structural properties of proteins. Previously, we developed a statistical inference method, robust co-evolutionary analysis (RoCA), to reliably predict co-evolutionary sectors of proteins, while controlling for statistical errors caused by limited data. RoCA was demonstrated on multiple viral proteins, with the inferred sectors showing close correspondences with experimentally-known biochemical domains. To facilitate seamless use of RoCA and promote more widespread application to protein data, here we present a standalone cross-platform package "RocaSec" which features an easy-to-use GUI. The package only requires the multiple sequence alignment of a protein for inferring the co-evolutionary sectors. In addition, when information on the protein biochemical domains is provided, RocaSec returns the corresponding statistical association between the inferred sectors and biochemical domains.AVAILABILITY AND IMPLEMENTATION: The RocaSec software is publicly available under the MIT License at https://github.com/ahmedaq/RocaSec.SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Aspecto clínico: Predição / Prognóstico Idioma: Inglês Assunto da revista: Informática Médica Ano de publicação: 2019 Tipo de documento: Artigo País de afiliação: China