Variational approach to molecular kinetics

Cited by (307)

Items 101–200 of 307

1. Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode Discovery in Dynamical Systems
   Wei Chen, Hythem Sidky, Andrew L. Ferguson · 2019 · Journal of Chemical Physics
2. Elucidating molecular mechanisms of functional conformational changes of proteins via Markov state models
   Xiaowei Wang, Ilona Christy Unarta, Peter Pak‐Hang Cheung, Xuhui Huang · 2020 · Current Opinion in Structural Biology
3. Active Learning of the Conformational Ensemble of Proteins Using Maximum Entropy VAMPNets
   Diego E. Kleiman, Diwakar Shukla · 2023 · Journal of Chemical Theory and Computation
4. Optimal Data-Driven Estimation of Generalized Markov State Models for Non-Equilibrium Dynamics
   P. Koltai, Hao Wu, Frank Noé, C. Schütte · 2018 · De Computis
5. Generative learning for nonlinear dynamics
   William Gilpin · 2024 · Nature Reviews Physics
6. Error bounds for kernel-based approximations of the Koopman operator
   F. Philipp, M. Schaller, K. Worthmann, Sebastian Peitz, Feliks Nuske · 2023 · Applied and Computational Harmonic Analysis
7. Adaptive partitioning by local density-peaks: An efficient density-based clustering algorithm for analyzing molecular dynamics trajectories
   Song Liu, Lizhe Zhu, Fu Kit Sheong, Wei Wang, Xuhui Huang · 2016 · Journal of Computational Chemistry
8. Target search and recognition mechanisms of glycosylase AlkD revealed by scanning FRET-FCS and Markov state models
   Sijia Peng, Xiaowei Wang, Lu Zhang, Shanshan He, Xin Sheng Zhao, Xuhui Huang, Chunlai Chen · 2020 · Proceedings of the National Academy of Sciences
9. Variational Identification of Markovian Transition States
   Linda Martini, Adam Kells, Roberto Covino, Gerhard Hummer, Nicolae‐Viorel Buchete, Edina Rosta · 2017 · Physical Review X
10. Principal component trajectories for modeling spectrally continuous dynamics as forced linear systems.
    D. Dylewsky, E. Kaiser, S. Brunton, J. Kutz · 2020 · Physical Review E
11. The Isomeric Preference of an Atypical Dopamine Transporter Inhibitor Contributes to Its Selection of the Transporter Conformation
    Ara M. Abramyan, Sebastian Stolzenberg, Zheng Li, Claus Juul Loland, Frank Noé, Lei Shi · 2017 · ACS Chemical Neuroscience
12. Rapid Calculation of Molecular Kinetics Using Compressed Sensing
    Florian Litzinger, Lorenzo Boninsegna, Hao Wu, Feliks Nüske, Raajen Patel, Richard G. Baraniuk, Frank Noé, Cecilia Clementi · 2018 · Journal of Chemical Theory and Computation
13. Singular Value Decomposition (SVD)
    Steven L. Brunton, J. Nathan Kutz · 2019 · Cambridge University Press eBooks
14. Building insightful, memory-enriched models to capture long-time biochemical processes from short-time simulations
    Anthony J. Dominic, Thomas Sayer, Siqin Cao, Thomas E. Markland, Xuhui Huang, Andrés Montoya−Castillo · 2023 · Proceedings of the National Academy of Sciences
15. A critical appraisal of Markov state models
    Ch. Schütte, Marco Sarich · 2015 · The European Physical Journal Special Topics
16. A kernel-based approach to molecular conformation analysis
    Stefan Klus, Andreas Bittracher, I. Schuster, C. Schütte · 2018 · Journal of Chemical Physics
17. Integrated Variational Approach to Conformational Dynamics: A Robust Strategy for Identifying Eigenfunctions of Dynamical Operators
    Chatipat Lorpaiboon, E. Thiede, R. Webber, J. Weare, A. Dinner · 2020 · Journal of Physical Chemistry B
18. Communication: Consistent interpretation of molecular simulation kinetics using Markov state models biased with external information.
    J. F. Rudzinski, K. Kremer, Tristan Bereau · 2016 · Journal of Chemical Physics
19. Protein Folding Free Energy Landscape along the Committor - the Optimal Folding Coordinate
    Sergei V. Krivov · 2018 · Journal of Chemical Theory and Computation
20. Identification of kinetic order parameters for non-equilibrium dynamics
    Fabian Paul, Hao Wu, Maximilian Vossel, Bert L. de Groot, Frank Noé · 2019 · The Journal of Chemical Physics
21. Towards tensor-based methods for the numerical approximation of the Perron--Frobenius and Koopman operator
    Stefan Klus, Christof Schütte · 2016 · Journal of Computational Dynamics
22. Memory Unlocks the Future of Biomolecular Dynamics: Transformative Tools to Uncover Physical Insights Accurately and Efficiently
    Anthony J. Dominic, Siqin Cao, Andrés Montoya−Castillo, Xuhui Huang · 2023 · Journal of the American Chemical Society
23. Beyond expectations: residual dynamic mode decomposition and variance for stochastic dynamical systems
    Matthew J. Colbrook, Qin Li, Ryan V. Raut, Alex Townsend · 2023 · Nonlinear Dynamics
24. MSM/RD: Coupling Markov state models of molecular kinetics with reaction-diffusion simulations
    Manuel Dibak, Mauricio J. del Razo, David De Sancho, Christof Schütte, Frank Noé · 2018 · The Journal of Chemical Physics
25. Recruiting machine learning methods for molecular simulations of proteins
    S. Mittal, D. Shukla · 2018 · Molecular Simulation
26. Common Nearest Neighbor Clustering—A Benchmark
    Oliver Lemke, Bettina G. Keller · 2018 · Algorithms
27. ExEnDiff: An Experiment-Guided Diffusion Model for Protein Conformational Ensemble Generation
    Liu, Yikai, Yu, Zongxin, Lindsay, Richard J., Lin, Guang, Chen, Ming, Sahoo, Abhilash, Hanson, Sonya M. · 2025 · PRX Life
28. Predicting efficacy of drug-carrier nanoparticle designs for cancer treatment: a machine learning-based solution
    Md Raisul Kibria, R. Akbar, Poonam Nidadavolu, O. Havryliuk, Sébastien Lafond, Sepinoud Azimi · 2023 · Scientific Reports
29. Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model
    Thomas R. Sisk, Paul Robustelli · 2024 · Proceedings of the National Academy of Sciences
30. Assessment and optimization of collective variables for protein conformational landscape: GB1 β -hairpin as a case study
    Navjeet Ahalawat, Jagannath Mondal · 2018 · The Journal of Chemical Physics
31. A Basis Set for Peptides for the Variational Approach to Conformational Kinetics
    F. Vitalini, Frank Noé, Bettina G. Keller · 2015 · Journal of Chemical Theory and Computation
32. Temporally Coherent Backmapping of Molecular Trajectories From Coarse-Grained to Atomistic Resolution
    Kirill Shmilovich, Marc Stieffenhofer, Nicholas E. Charron, Moritz Hoffmann · 2022 · The Journal of Physical Chemistry A
33. Data-Driven Control: Theory and Applications
    Damoon Soudbakhsh, Anuradha M. Annaswamy, Yan Wang, Steven L. Brunton, Joseph E. Gaudio, Heather S. Hussain, Draguna Vrabie, Ján Drgoňa, Dimitar Filev · 2023 · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference
34. Nonparametric variational optimization of reaction coordinates
    Polina V. Banushkina, Sergei V. Krivov · 2015 · The Journal of Chemical Physics
35. Girsanov Reweighting Enhanced Sampling Technique (GREST): On-the-Fly Data-Driven Discovery of and Enhanced Sampling in Slow Collective Variables
    Kirill Shmilovich, Andrew L. Ferguson · 2023 · The Journal of Physical Chemistry A
36. Recent advances in describing and driving crystal nucleation using machine learning and artificial intelligence
    Eric R. Beyerle, Ziyue Zou, Pratyush Tiwary · 2023 · Current Opinion in Solid State and Materials Science
37. The multiverse of dynamic mode decomposition algorithms
    Matthew J. Colbrook · 2024 · Handbook of numerical analysis
38. Estimation of the infinitesimal generator by square-root approximation
    Luca Donati, Martin Heida, Bettina G. Keller, Marcus Weber · 2018 · Journal of Physics Condensed Matter
39. An Information Bottleneck Approach for Markov Model Construction
    De-Di Wang, Yunrui Qiu, E. Beyerle, Xu-Hui Huang, P. Tiwary · 2024 · Journal of Chemical Theory and Computation
40. Structural Ensemble of the Insulin Monomer
    Luis Busto‐Moner, Chi-Jui Feng, Adam Antoszewski, Andrei Tokmakoff, Aaron R. Dinner · 2021 · Biochemistry
41. Confronting pitfalls of AI-augmented molecular dynamics using statistical physics
    Shashank Pant, Zachary Smith, Yihang Wang, Emad Tajkhorshid, Pratyush Tiwary · 2020 · The Journal of Chemical Physics
42. Molecular dynamics simulations data of the twenty encoded amino acids in different force fields
    Francesca Vitalini, F. Noé, Bettina Keller · 2016 · Data in Brief
43. Nearly reducible finite Markov chains: Theory and algorithms
    Daniel Sharpe, David J. Wales · 2021 · The Journal of Chemical Physics
44. Slicing and Dicing: Optimal Coarse-Grained Representation to Preserve Molecular Kinetics
    Wang-Fei Yang, C. Templeton, David Rosenberger, Andreas Bittracher, F. Nüske, Frank Noé, Cecilia Clementi · 2023 · ACS Central Science
45. Ligand-bound glutamine binding protein assumes multiple metastable binding sites with different binding affinities
    Lu Zhang, Shaowen Wu, Yitao Feng, Dan Wang, Xilin Jia, Zhijun Liu, Jianwei Liu, Wenning Wang · 2020 · Communications Biology
46. Selecting Features for Markov Modeling: A Case Study on HP35
    Daniel Nagel, Sofia Sartore, Gerhard Stock · 2023 · Journal of Chemical Theory and Computation
47. The E2.65A mutation disrupts dynamic binding poses of SB269652 at the dopamine D2 and D3 receptors
    Ravi Kumar Verma, Ara M. Abramyan, M. Michino, R. Free, David R. Sibley, J. Javitch, J. R. Lane, Lei Shi · 2018 · PLoS Comput. Biol.
48. Independent Markov decomposition: Toward modeling kinetics of biomolecular complexes
    Tim Hempel, Mauricio J. del Razo, Christopher T. Lee, Bryn C. Taylor, Rommie E. Amaro, Frank Noé · 2021 · Proceedings of the National Academy of Sciences
49. Atomic resolution of short-range sliding dynamics of thymine DNA glycosylase along DNA minor-groove for lesion recognition
    Jiaqi Tian, Lingyan Wang, Lin-Tai Da · 2021 · Nucleic Acids Research
50. A review of Girsanov reweighting and of square root approximation for building molecular Markov state models
    Luca Donati, Marcus Weber, Bettina G. Keller · 2022 · Journal of Mathematical Physics
51. Dimensional reduction of Markov state models from renormalization group theory.
    Simone Orioli, P. Faccioli · 2016 · Journal of Chemical Physics
52. Machine Learning at the Interface of Polymer Science and Biology: How Far Can We Go?
    Eleonora Gianti, Simona Percec · 2022 · Biomacromolecules
53. Analytical methods for structural ensembles and dynamics of intrinsically disordered proteins
    Marieke Schor, Antonia S. J. S. Mey, Cait E. MacPhee · 2016 · Biophysical Reviews
54. Markov models of the apo-MDM2 lid region reveal diffuse yet two-state binding dynamics and receptor poses for computational docking
    Mukherjee, Sudipto, Pantelopulos, George A., Voelz, Vincent A. · 2016 · Scientific Reports
55. Extensible and Scalable Adaptive Sampling on Supercomputers
    Eugen Hruška, Vivekanandan Balasubramanian, Hyungro Lee, Shantenu Jha, Cecilia Clementi · 2020 · Journal of Chemical Theory and Computation
56. Tensor-based computation of metastable and coherent sets
    F. Nüske, Patrick Gelß, Stefan Klus, Cecilia Clementi · 2019 · Physica A: Statistical Mechanics and its Applications
57. Markov models from the square root approximation of the Fokker–Planck equation: calculating the grid-dependent flux
    Luca Donati, Marcus Weber, Bettina G. Keller · 2020 · Journal of Physics Condensed Matter
58. Manifold learning in atomistic simulations: a conceptual review
    Jakub Rydzewski, Ming Chen, Ómar Valsson · 2023 · Machine Learning Science and Technology
59. Toward a Benchmark for Markov State Models: The Folding of HP35
    Daniel Nagel, Sofia Sartore, Gerhard Stock · 2023 · The Journal of Physical Chemistry Letters
60. Koopman analysis of quantum systems
    Stefan Klus, F. Nüske, Sebastian Peitz · 2022 · Journal of Physics A Mathematical and Theoretical
61. Efficient approximation of molecular kinetics using random Fourier features.
    F. Nüske, Stefan Klus · 2023 · Journal of Chemical Physics
62. A Minimum Variance Clustering Approach Produces Robust and Interpretable Coarse-Grained Models
    Brooke E. Husic, Keri A. McKiernan, Hannah K. Wayment-Steele, Mohammad Muneeb Sultan, Vijay S. Pande · 2017 · Journal of Chemical Theory and Computation
63. Landmark Kernel tICA for Conformational Dynamics
    M. Harrigan, V. Pande · 2017 · bioRxiv
64. Predicting Optimal DEER Label Positions to Study Protein Conformational Heterogeneity.
    S. Mittal, D. Shukla · 2017 · Journal of Physical Chemistry B
65. Kinetic network models to study molecular self-assembly in the wake of machine learning
    Bo-Jun Liu, Yunrui Qiu, Eshani C. Goonetilleke, Xu-Hui Huang · 2022 · MRS bulletin
66. Finding Dominant Structures of Nonreversible Markov Processes
    N. D. Conrad, Marcus Weber, C. Schütte · 2016 · Multiscale Modeling & simulation
67. Path lumping: An efficient algorithm to identify metastable path channels for conformational dynamics of multi-body systems
    Luming Meng, Fu Kit Sheong, Xiangze Zeng, Lizhe Zhu, Xuhui Huang · 2017 · The Journal of Chemical Physics
68. Recovery of Protein Folding Funnels from Single-Molecule Time Series by Delay Embeddings and Manifold Learning
    Jiang Wang, Andrew L. Ferguson · 2018 · The Journal of Physical Chemistry B
69. Estimation of Koopman Transfer Operators for the Equatorial Pacific SST
    Antonio Navarra, Joe Tribbia, Stefan Klus · 2021 · Journal of the Atmospheric Sciences
70. Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event prediction.
    J. Strahan, Spencer C. Guo, Chatipat Lorpaiboon, A. Dinner, J. Weare · 2023 · Journal of Chemical Physics
71. Reaction coordinate flows for model reduction of molecular kinetics
    Hao Wu, Frank Noé · 2024 · The Journal of Chemical Physics
72. Physics-informed and data-driven discovery of governing equations for complex phenomena in heterogeneous media
    Muhammad Sahimi · 2024 · Physical review. E
73. Set-free Markov state model building.
    Marcus Weber, K. Fackeldey, C. Schütte · 2017 · Journal of Chemical Physics
74. SAPPHIRE-based clustering.
    F. Cocina, A. Vitalis, A. Caflisch · 2020 · Journal of Chemical Theory and Computation
75. Path probability ratios for Langevin dynamics—Exact and approximate
    Stefanie Kieninger, Bettina G. Keller · 2021 · The Journal of Chemical Physics
76. Solving eigenvalue PDEs of metastable diffusion processes using artificial neural networks
    Wei Zhang, Tiejun Li, C. Schütte · 2021 · Journal of Computational Physics
77. Gaussian Markov transition models of molecular kinetics
    Hao Wu, Frank Noé · 2015 · The Journal of Chemical Physics
78. Conserve Water: A Method for the Analysis of Solvent in Molecular Dynamics.
    M. Harrigan, D. Shukla, V. Pande · 2015 · Journal of Chemical Theory and Computation
79. Deep-Learning-Assisted Enhanced Sampling for Exploring Molecular Conformational Changes
    Haohao Fu, Han Liu, Jingya Xing, Tong Zhou Zhao, Xueguang Shao, Wensheng Cai · 2023 · The Journal of Physical Chemistry B
80. Transfer Learning from Markov Models Leads to Efficient Sampling of Related Systems
    Mohammad Muneeb Sultan, Vijay S. Pande · 2017 · The Journal of Physical Chemistry B
81. Solution-State Preorganization of Cyclic β-Hairpin Ligands Determines Binding Mechanism and Affinities for MDM2
    Yunhui Ge, Si Zhang, Máté Erdélyi, Vincent A. Voelz · 2021 · Journal of Chemical Information and Modeling
82. TYROSINE KINASES: COMPLEX MOLECULAR SYSTEMS CHALLENGING COMPUTATIONAL METHODOLOGIES
    Trayder Thomas, B. Roux · 2021 · European Physical Journal B : Condensed Matter Physics
83. Analyzing Multimodal Probability Measures with Autoencoders
    Tony Lelièvre A, Thomas Pigeon, Gabriel Stoltz, Zhang Wei · 2024 · The Journal of Physical Chemistry B
84. tICA-Metadynamics for Identifying Slow Dynamics in Membrane Permeation
    Myongin Oh, G. C. A. da Hora, Jessica M. J. Swanson · 2023 · Journal of Chemical Theory and Computation
85. Projected metastable Markov processes and their estimation with observable operator models
    Hao Wu, Jan-Hendrik Prinz, Frank Noé · 2015 · The Journal of Chemical Physics
86. Reliable Approximation of Long Relaxation Timescales in Molecular Dynamics
    Wei Zhang, C. Schütte · 2017 · Entropy
87. Foundations of Time Dependent Quantum Dynamics of Molecules Under Isolation and in Coherent Electromagnetic Fields
    Roberto R. Marquardt, Martin Qüack · 2020 · Elsevier eBooks
88. Progress in deep Markov state modeling: Coarse graining and experimental data restraints
    Andreas Mardt, Frank Noé · 2021 · The Journal of Chemical Physics
89. Exploring glassy dynamics with Markov state models from graph dynamical neural networks.
    S. Soltani, C. Sinclair, Joerg Rottler · 2021 · Physical Review E
90. Another look at residual dynamic mode decomposition in the regime of fewer snapshots than dictionary size
    Matthew J. Colbrook · 2024 · Physica D Nonlinear Phenomena
91. Kernel Embedding Based Variational Approach for Low-Dimensional Approximation of Dynamical Systems
    Wenchong Tian, Hao Wu · 2020 · Comput. Methods Appl. Math.
92. Computational and Experimental Evaluation of Designed β-Cap Hairpins Using Molecular Simulations and Kinetic Network Models
    Yun-Hui Ge, B. Kier, N. Andersen, Vincent A. Voelz · 2017 · Journal of Chemical Information and Modeling
93. From metastable to coherent sets- Time-discretization schemes.
    K. Fackeldey, P. Koltai, P. Névir, H. Rust, A. Schild, Marcus Weber · 2019 · Chaos
94. Fourier and Wavelet Transforms
    Steven L. Brunton, J. Nathan Kutz · 2019 · Cambridge University Press eBooks
95. Constructing Kinetic Network Models to Elucidate Mechanisms of Functional Conformational Changes of Enzymes and Their Recognition with Ligands
    Lu Zhang, Hanlun Jiang, Fu Kit Sheong, Fátima Pardo‐Ávila, Peter Pak‐Hang Cheung, Xuhui Huang · 2016 · Methods in enzymology on CD-ROM/Methods in enzymology
96. Markov State Model of Lassa Virus Nucleoprotein Reveals Large Structural Changes During the Trimer to Monomer Transition
    Jason G. Pattis, Eric R. May · 2020 · Structure
97. Ensemble Adaptive Sampling Scheme: Identifying an Optimal Sampling Strategy via Policy Ranking
    Hassan Nadeem, Diwakar Shukla · 2025 · Journal of Chemical Theory and Computation
98. Error Analysis of Kernel EDMD for Prediction and Control in the Koopman Framework
    Friedrich Philipp, Manuel Schaller, Karl Worthmann, Sebastian Peitz, Feliks Nüske · 2025 · Journal of Nonlinear Science
99. Molecular Latent Space Simulators for Distributed and Multimolecular Trajectories
    Michael S. Jones, Zachary A. McDargh, Rafal Wiewiora, Jesús A. Izaguirre, Huafeng Xu, Andrew L. Ferguson · 2023 · The Journal of Physical Chemistry A
100. Systematically Constructing Kinetic Transition Network in Polypeptide from Top to Down: Trajectory Mapping
     Linchen Gong, Xin Zhou, Zhongcan Ouyang · 2015 · PLoS ONE