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Adaptive spectral clustering for conformation analysis

Please always quote using this URN:urn:nbn:de:0296-matheon-10430
  • Markov state models have become very popular for the description of conformation dynamics of molecules over long timescales. The construction of such models requires a partitioning of the configuration space such that the discretization can serve as an approximation of metastable conformations. Since the computational complexity for the construction of a Markov state model increases quadratically with the number of sets, it is desirable to obtain as few sets as necessary. In this paper we propose an algorithm for the adaptive refinement of an initial coarse partitioning. A spectral clustering method is applied to the final partitioning to detect the metastable conformations. We apply this method to the conformation analysis of a model tri-peptide molecule, where metastable beta- and gamma-turn conformations can be identified.

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Metadaten
Author:Marcus Weber, Fiete Haack, Susanna Röblitz, Olga Scharkoi, Burkhard Schmidt
URN:urn:nbn:de:0296-matheon-10430
Referee:Peter Deuflhard
Document Type:Preprint, Research Center Matheon
Language:English
Date of first Publication:2012/01/31
Release Date:2012/01/31
Tag:
Institute:Freie Universität Berlin
Zuse Institute Berlin (ZIB)
MSC-Classification:60-XX PROBABILITY THEORY AND STOCHASTIC PROCESSES (For additional applications, see 11Kxx, 62-XX, 90-XX, 91-XX, 92-XX, 93-XX, 94-XX) / 60Jxx Markov processes / 60J05 Discrete-time Markov processes on general state spaces
Preprint Number:906
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