J
Jan-Hendrik Prinz
Researcher at Free University of Berlin
Publications - 29
Citations - 2909
Jan-Hendrik Prinz is an academic researcher from Free University of Berlin. The author has contributed to research in topics: Markov chain & Markov model. The author has an hindex of 18, co-authored 29 publications receiving 2383 citations. Previous affiliations of Jan-Hendrik Prinz include Kettering University & Heidelberg University.
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Journal ArticleDOI
Markov models of molecular kinetics: Generation and validation
Jan-Hendrik Prinz,Hao Wu,Marco Sarich,Bettina G. Keller,Martin Senne,Martin Held,John D. Chodera,Christof Schütte,Frank Noé +8 more
TL;DR: An upper bound for the approximation error made by modeling molecular dynamics with a Markov chain is described and it is shown that this error can be made arbitrarily small with surprisingly little effort.
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PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models.
Martin K. Scherer,Benjamin Trendelkamp-Schroer,Fabian Paul,Guillermo Pérez-Hernández,Moritz Hoffmann,Nuria Plattner,Christoph Wehmeyer,Jan-Hendrik Prinz,Frank Noé +8 more
TL;DR: The open-source Python package PyEMMA is presented, derived a systematic and accurate way to coarse-grain MSMs to few states and to illustrate the structures of the metastable states of the system.
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Projected and hidden Markov models for calculating kinetics and metastable states of complex molecules.
TL;DR: It is shown how various molecular observables of interest that are often computed from MSMs can be computed from HMMs/PMMs, and a practically feasible approximation via Hidden Markov Models (HMMs) is derived.
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Probing molecular kinetics with Markov models: metastable states, transition pathways and spectroscopic observables
TL;DR: Transition path theory is described which allows the entire ensemble of protein folding pathways to be investigated and that combines naturally with Markov models, by which experimentally observable timescales can be equipped with an understanding of the structural rearrangement processes that take place at these timescale.
Journal ArticleDOI
Projected and Hidden Markov Models for calculating kinetics and metastable states of complex molecules
TL;DR: Projected Markov Models (PMMs) as mentioned in this paper were proposed to approximate the true dynamics by assuming a Markov chain on a clusters discretization of the state space, which is difficult to make for highdimensional biomolecular systems, and the quality and reproducibility of MSMs has therefore been limited.