Haack, F. and Röblitz, S. and Scharkoi, O. and Schmidt, B. and Weber, M. (2010) Adaptive spectral clustering for conformation analysis. In: ICNAAM 2010: International Conference of Numerical Analysis and Applied Mathematics. AIP Conf. Proc. (1281). AIP, pp. 15851588.
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Official URL: http://dx.doi.org/10.1063/1.3498116
Abstract
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 tripeptide molecule, where metastable β and γturn conformations can be identified.
Item Type:  Book Section 

Subjects:  Physical Sciences > Chemistry > Physical Chemistry Mathematical and Computer Sciences > Mathematics > Applied Mathematics Physical Sciences > Physics > Chemical Physics 
Divisions:  Department of Mathematics and Computer Science > Institute of Mathematics > BioComputing Group 
ID Code:  919 
Deposited By:  Burkhard Schmidt 
Deposited On:  26 Jul 2010 14:18 
Last Modified:  03 Mar 2017 14:40 
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