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CopomuS-Ranking Compensatory Mutations to Guide RNA-RNA Interaction Verification Experiments.
Raden, Martin; Gutmann, Fabio; Uhl, Michael; Backofen, Rolf.
Afiliación
  • Raden M; Bioinformatics, Department of Computer Science, University Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.
  • Gutmann F; Bioinformatics, Department of Computer Science, University Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.
  • Uhl M; Bioinformatics, Department of Computer Science, University Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.
  • Backofen R; Bioinformatics, Department of Computer Science, University Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany.
Int J Mol Sci ; 21(11)2020 May 28.
Article en En | MEDLINE | ID: mdl-32481751
ABSTRACT
In silico RNA-RNA interaction prediction is widely applied to identify putative interaction partners and to assess interaction details in base pair resolution. To verify specific interactions, in vitro evidence can be obtained via compensatory mutation experiments. Unfortunately, the selection of compensatory mutations is non-trivial and typically based on subjective ad hoc decisions. To support the decision process, we introduce our COmPensatOry MUtation Selector CopomuS. CopomuS evaluates the effects of mutations on RNA-RNA interaction formation using a set of objective criteria, and outputs a reliable ranking of compensatory mutation candidates. For RNA-RNA interaction assessment, the state-of-the-art IntaRNA prediction tool is applied. We investigate characteristics of successfully verified RNA-RNA interactions from the literature, which guided the design of CopomuS. Finally, we evaluate its performance based on experimentally validated compensatory mutations of prokaryotic sRNAs and their target mRNAs. CopomuS predictions highly agree with known results, making it a valuable tool to support the design of verification experiments for RNA-RNA interactions. It is part of the IntaRNA package and available as stand-alone webserver for ad hoc application.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / ARN / ARN Bacteriano / Biología Computacional / Mutación Tipo de estudio: Prognostic_studies Idioma: En Revista: Int J Mol Sci Año: 2020 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / ARN / ARN Bacteriano / Biología Computacional / Mutación Tipo de estudio: Prognostic_studies Idioma: En Revista: Int J Mol Sci Año: 2020 Tipo del documento: Article País de afiliación: Alemania
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