Hybrid Monte Carlo with adaptive temperature in a mixed canonical ensemble: efficient conformational analysis of RNA

Abstract: "A hybrid Monte Carlo method with adaptive temperature choice is presented, which exactly generates the distribution of a mixed-canonical ensemble composed of two canonical ensembles at low and high temperature. The analysis of resulting Markov chains with the reweighting technique sh...

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Bibliographische Detailangaben
Hauptverfasser: Fischer, Alexander (VerfasserIn), Cordes, Frank (VerfasserIn), Schütte, Christof 1966- (VerfasserIn)
Format: Buch
Sprache:English
Veröffentlicht: Berlin Konrad-Zuse-Zentrum für Informationstechnik 1997
Schriftenreihe:Preprint SC / Konrad-Zuse-Zentrum für Informationstechnik Berlin 1997,67
Schlagworte:
Zusammenfassung:Abstract: "A hybrid Monte Carlo method with adaptive temperature choice is presented, which exactly generates the distribution of a mixed-canonical ensemble composed of two canonical ensembles at low and high temperature. The analysis of resulting Markov chains with the reweighting technique shows an efficient sampling of the canonical distribution at low temperature, whereas the high temperature component facilitates conformational transitions, which allows shorter simulation times. The algorithm was tested by comparing analytical and numerical results for the small n-butane molecule before simulations were performed for a triribonucleotide. Sampling the complex multi-minima energy landscape of this small RNA segment, we observe enforced crossing of energy barriers."
Beschreibung:15 S. Ill., graph. Darst.

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