Johannes Schmidt-Ehrenberg

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The bioactivity of a molecule strongly depends on its metastable conformational shapes and the transitions between these. Therefore, conformation analysis and visualization is a basic prerequisite for the understanding of biochemical processes.We present techniques for visual analysis of metastable molecular conformations. Core of these are flexibly(More)
Decomposition of the high dimensional conformational space of biomolecules into metastable subsets is used for data reduction of long molecular trajectories in order to facilitate chemical analysis and to improve convergence of simulations within these subsets. The metastability is identified by the Perron-Cluster Cluster Analysis of a Markov process that(More)
We present a method for simultaneous dimension reduction and metastability analysis of high dimensional time series. The approach is based on the combination of hidden Markov models (HMMs) and principal component analysis. We derive optimal estimators for the loglikelihood functional and employ the Expectation Maximization algorithm for its numerical(More)
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