CMV: visualization for RNA and protein family models and their comparisons.
Bioinformatics
; 34(15): 2676-2678, 2018 08 01.
Article
em En
| MEDLINE
| ID: mdl-29554223
ABSTRACT
Summary:
A standard method for the identification of novel RNAs or proteins is homology search via probabilistic models. One approach relies on the definition of families, which can be encoded as covariance models (CMs) or Hidden Markov Models (HMMs). While being powerful tools, their complexity makes it tedious to investigate them in their (default) tabulated form. This specifically applies to the interpretation of comparisons between multiple models as in family clans. The Covariance model visualization tools (CMV) visualize CMs or HMMs to I) Obtain an easily interpretable representation of HMMs and CMs; II) Put them in context with the structural sequence alignments they have been created from; III) Investigate results of model comparisons and highlight regions of interest. Availability and implementation Source code (http//www.github.com/eggzilla/cmv), web-service (http//rna.informatik.uni-freiburg.de/CMVS). Supplementary information Supplementary data are available at Bioinformatics online.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Conformação Proteica
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Software
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Alinhamento de Sequência
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Análise de Sequência de RNA
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Análise de Sequência de Proteína
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Conformação de Ácido Nucleico
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article