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Article

Swenson, D.W.H. and Prinz, J.-H. and Noé, F. and Chodera, J. D. and Bolhuis, P.G. (2018) OpenPathSampling: A Python Framework for Path Sampling Simulations. 1. Basics. Journal of Chemical Theory and Computation, Article ASAP . ISSN 1549-9618, ESSN: 15-49-9626

Swenson, D.W.H. and Prinz, J.-H. and Noé, F. and Chodera, J. D. and Bolhuis, P.G. (2018) OpenPathSampling: A Python Framework for Path Sampling Simulations. 2. Building and Customizing Path Ensembles and Sample Schemes. Journal of Chemical Theory and Computation, Article ASAP . ISSN 1549-9618, ESSN: 15-49-9626

Wu, H. and Prinz, J.-H. and Noé, F. (2015) Projected Metastable Markov Processes and Their Estimation with Observable Operator Models. J. Chem. Phys., 143 (14). p. 144101.

Scherer, M. K. and Trendelkamp-Schroer, B. and Paul, F. and Pérez-Hernández, G. and Hoffmann, M. and Plattner, N. and Wehmeyer, C. and Prinz, J.-H. and Noé, F. (2015) PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models. J. Chem. Theory Comput., 11 (11). pp. 5525-5542.

Prinz, J.-H. and Chodera, J. D. and Noé, F. (2014) Spectral rate theory for two-state kinetics. Phys Rev X, 4 . 011020.

Lindner, Benjamin and Yi, Zheng and Prinz, J.-H. and Smith, J. C. and Noé, F. (2013) Dynamic Neutron Scattering from Conformational Dynamics I: Theory and Markov models. J. Chem. Phys., 139 . p. 175101.

Yi, Zheng and Lindner, Benjamin and Prinz, J.-H. and Noé, F. and Smith, J. C. (2013) Dynamic Neutron Scattering from Conformational Dynamics II: Application using Molecular Dynamics Simulation and Markov modeling. J. Chem. Phys., 139 . p. 175102.

Noé, F. and Wu, H. and Prinz, J.-H. and Plattner, N. (2013) Projected and Hidden Markov Models for calculating kinetics and metastable states of complex molecules. J. Chem. Phys., 139 . p. 184114.

Keller, B. and Prinz, J.-H. and Noé, F. (2012) Markov models and dynamical fingerprints: unraveling the complexity of molecular kinetics. Chem. Phys., 396 . pp. 92-107.

Keller, B. and Prinz, J.-H. and Noé, F. (2012) Resolving the apparent gap in complexity between simulated and measured kinetics of biomolecules. From Computational Biophysics to Systems Biology (CBSB11) Proceedings, IAS Series, 8 . pp. 61-64.

Prinz, J.-H. and Wu, H. and Sarich, M. and Keller, B. and Senne, M. and Held, M. and Chodera, J. D. and Schütte, Ch. and Noé, F. (2011) Markov models of molecular kinetics: Generation and Validation. J. Chem. Phys., 134 . p. 174105.

Held, M. and Metzner, Ph. and Prinz, J.-H. and Noé, F. (2011) Mechanisms of Protein-Ligand association and its modulation by protein mutations. Biophys. J., 100 (3). pp. 701-710.

Chodera, J. D. and Swope, W. D. and Noé, F. and Prinz, J.-H. and Shirts, M. R. and Pande, V. S. (2011) Dynamical reweighting: Improved estimates of dynamical properties from simulations at multiple temperatures. J. Chem. Phys., 134 (24). p. 244107.

Prinz, J.-H. and Held, M. and Smith, J. C. and Noé, F. (2011) Efficient Computation, Sensitivity and Error Analysis of Committor Probabilities for Complex Dynamical Processes. Multiscale Model. Simul., 9 . pp. 545-567.

Prinz, J.-H. and Chodera, J. D. and Pande, V. S. and Swope, W. D. and Smith, J. C. and Noé, F. (2011) Optimal use of data in parallel tempering simulations for the construction of discrete-state Markov models of biomolecular dynamics. J. Chem. Phys., 134 (24). p. 244108.

Prinz, J.-H. and Keller, B. and Noé, F. (2011) Probing molecular kinetics with Markov models: Metastable states, transition pathways and spectroscopic observables. Phys. Chem. Chem. Phys., 13 . pp. 16912-16927.

Book Section

Noé, F. and Prinz, J.-H. (2014) Analysis of Markov Models. In: An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation. Advances in Experimental Medicine and Biology, 797 . Springer, pp. 75-90.

Prinz, J.-H. and Chodera, J. D. and Noé, F. (2014) Estimation and Validation of Markov Models. In: An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation. Advances in Experimental Medicine and Biology , 797 . Springer, pp. 45-60.

Sarich, M. and Prinz, J.-H. and Schütte, Ch. (2014) Markov Model Theory. In: An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation. Advances in Experimental Medicine and Biology, 797 (797). Springer, Dordrecht, Heidelberg, New York, London, pp. 23-44. ISBN 978-94-007-7605-0

Thesis

Prinz, J.-H. (2012) Advanced estimation methods for Markov models of dynamical systems. PhD thesis, FU Berlin.