Repository: Freie Universität Berlin, Math Department

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Number of items: 13.

2019

Paul, F. and Wu, H. and Vossel, M. and de Groot, B.L. and Noé, F. (2019) Identification of kinetic order parameters for non-equilibrium dynamics. J. Chem. Phys., 150 (16). p. 164120. ISSN 0021-9606, ESSN: 1089-7690

Pinamonti, G. and Paul, F. and Noé, F. and Rodriguez, A. and Bussi, G. (2019) The mechanism of RNA base fraying: Molecular dynamics simulations analyzed with core-set Markov state models. J. Chem. Phys., 150 (15). p. 154123. ISSN 0021-9606, ESSN: 1089-7690

2018

Scherer, M. K. and Husic, B.E. and Hoffmann, M. and Paul, F. and Wu, H. and Noé, F. (2018) Variational Selection of Features for Molecular Kinetics. SFB 1114 Preprint in arXiv:1811.11714 . pp. 1-12. (Unpublished)

Paul, F. and Noé, F. and Weikl, T. (2018) Identifying Conformational-Selection and Induced-Fit Aspects in the Binding-Induced Folding of PMI from Markov State Modeling of Atomistic Simulations. J. Phys. Chem. B .

2017

Paul, F. and Wehmeyer, C. and Abualrous, E. T. and Wu, H. and Crabtree, M. D. and Schöneberg, J. and Clarke, J. and Freund, C. and Weikl, T. and Noé, F. (2017) Protein-peptide association kinetics beyond the seconds timescale from atomistic simulations. Nat. Comm., 8 (1095).

Olsson, Simon and Wu, H. and Paul, F. and Clementi, C. and Noé, F. (2017) Combining experimental and simulation data of molecular processes via augmented Markov models. Proc. Natl. Acad. Sci. USA, 114 . pp. 8265-8270.

Pinamonti, G. and Zhao, J. and Condon, D. and Paul, F. and Noé, F. and Turner, D. and Bussi, G. (2017) Predicting the kinetics of RNA oligonucleotides using Markov state models. J. Chem. Theory Comput., 13 (2). pp. 926-934.

Wu, H. and Nüske, F. and Paul, F. and Klus, S. and Koltai, Péter and Noé, F. (2017) Variational Koopman models: slow collective variables and molecular kinetics from short off-equilibrium simulations. J. Chem. Phys., 146 . p. 154104.

2016

Wu, H. and Paul, F. and Wehmeyer, C. and Noé, F. (2016) Multiensemble Markov models of molecular thermodynamics and kinetics. Proceedings of the National Academy of Sciences, 113 (23). E3221-E3230 . ISSN 0027-8424

Paul, F. and Weikl, T. (2016) How to Distinguish Conformational Selection and Induced Fit Based on Chemical Relaxation Rates. PLOS Computational Biology .

2015

Trendelkamp-Schroer, B. and Wu, H. and Paul, F. and Noé, F. (2015) Estimation and uncertainty of reversible Markov models. J. Chem. Phys., 143 (17). p. 174101.

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.

2013

Pérez-Hernández, G. and Paul, F. and Giorgino, T. and de Fabritiis, G. and Noé, F. (2013) Identification of slow molecular order parameters for Markov model construction. J. Chem. Phys., 139 . 015102.

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