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Basin Hopping Graph: a computational framework to characterize RNA folding landscapes.
Kucharík, Marcel; Hofacker, Ivo L; Stadler, Peter F; Qin, Jing.
Afiliación
  • Kucharík M; Institute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Compu
  • Hofacker IL; Institute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Compu
  • Stadler PF; Institute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Compu
  • Qin J; Institute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Compu
Bioinformatics ; 30(14): 2009-17, 2014 Jul 15.
Article en En | MEDLINE | ID: mdl-24648041
MOTIVATION: RNA folding is a complicated kinetic process. The minimum free energy structure provides only a static view of the most stable conformational state of the system. It is insufficient to give detailed insights into the dynamic behavior of RNAs. A sufficiently sophisticated analysis of the folding free energy landscape, however, can provide the relevant information. RESULTS: We introduce the Basin Hopping Graph (BHG) as a novel coarse-grained model of folding landscapes. Each vertex of the BHG is a local minimum, which represents the corresponding basin in the landscape. Its edges connect basins when the direct transitions between them are 'energetically favorable'. Edge weights endcode the corresponding saddle heights and thus measure the difficulties of these favorable transitions. BHGs can be approximated accurately and efficiently for RNA molecules well beyond the length range accessible to enumerative algorithms. AVAILABILITY AND IMPLEMENTATION: The algorithms described here are implemented in C++ as standalone programs. Its source code and supplemental material can be freely downloaded from http://www.tbi.univie.ac.at/bhg.html.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Pliegue del ARN Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2014 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Pliegue del ARN Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2014 Tipo del documento: Article