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Automatic Identification of Metastable Conformations via Self-Organized Neural Networks

Please always quote using this URN: urn:nbn:de:0297-zib-6197
  • As has been shown recently, the identification of metastable chemical conformations leads to a Perron cluster eigenvalue problem for a reversible Markov operator. Naive discretization of this operator would suffer from combinatorial explosion. As a first remedy, a pre-identification of essential degrees of freedom out of the set of torsion angles had been applied up to now. The present paper suggests a different approach based on neural networks: its idea is to discretize the Markov operator via self-organizing (box) maps. The thus obtained box discretization then serves as a prerequisite for the subsequent Perron cluster analysis. Moreover, this approach also permits exploitation of additional structure within embedded simulations. As it turns out, the new method is fully automatic and efficient also in the treatment of biomolecules. This is exemplified by numerical results.

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Metadaten
Author:Tobias Galliat, Peter Deuflhard, Rainer Roitzsch, Frank Cordes
Document Type:ZIB-Report
Tag:Molecular Dynamics; Monte-Carlo methods; Perron cluster; biochemical conformations; cluster analysis; operator discretization
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 / 60J20 Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) [See also 90B30, 91D10, 91D35, 91E40]
62-XX STATISTICS / 62Hxx Multivariate analysis [See also 60Exx] / 62H30 Classification and discrimination; cluster analysis [See also 68T10]
68-XX COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area) / 68Txx Artificial intelligence / 68T05 Learning and adaptive systems [See also 68Q32, 91E40]
92-XX BIOLOGY AND OTHER NATURAL SCIENCES / 92-08 Computational methods
Date of first Publication:2000/12/18
Series (Serial Number):ZIB-Report (00-51)
ZIB-Reportnumber:00-51
Published in:Appeared in: T. Schlick, H. H. Gan (eds.) Computational Methods for Macromolecules : Challenges and Applications. Proc. of the 3rd Int. Workshop on Methods for Macromolecular Modelling, New York 2000. Springer 2002. LNCSE 24, pp. 260-284
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