Repository: Freie Universität Berlin, Math Department

A kernel-based approach to molecular conformation analysis

Klus, S. and Bittracher, A. and Schuster, I. and Schütte, Ch. (2018) A kernel-based approach to molecular conformation analysis. Journal of Chemical Physics . ISSN 0021-9606 (Submitted)

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Abstract

We present a novel machine learning approach to understanding conformation dynamics of biomolecules. The approach combines kernel-based techniques that are popular in the machine learning community with transfer operator theory for analyzing dynamical systems in order to identify conformation dynamics based on molecular dynamics simulation data. We show that many of the prominent methods like Markov State Models, EDMD, and TICA can be regarded as special cases of this approach and that new efficient algorithms can be constructed based on this derivation. The results of these new powerful methods will be illustrated with several examples, in particular the alanine dipeptide and the protein NTL9.

Item Type:Article
Subjects:Mathematical and Computer Sciences
Mathematical and Computer Sciences > Mathematics
Divisions:Department of Mathematics and Computer Science > Institute of Mathematics
Department of Mathematics and Computer Science > Institute of Mathematics > BioComputing Group
ID Code:2334
Deposited By: BioComp Admin
Deposited On:26 Mar 2019 12:31
Last Modified:26 Mar 2019 12:32

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