Automatic Method for Identifying Reaction Coordinates in Complex Systems

Cited by (400)

Items 301–400 of 400

1. A Probabilistic Framework for Constructing Temporal Relations in Replica Exchange Molecular Trajectories
   Aditya Chattopadhyay, Min Zheng, Mark P. Waller, U. Deva Priyakumar · 2018 · Journal of Chemical Theory and Computation
2. Molecular dynamics analysis of biomolecular systems including nucleic acids
   Takeru Kameda, Akinori Awazu, Yuichi Togashi · 2022 · Biophysics and Physicobiology
3. Catching a protein in the act
   Gerhard Hummer · 2010 · Proceedings of the National Academy of Sciences
4. Reply to “Comment on 'Toward Identification of the Reaction Coordinate Directly from the Transition State Ensemble Using the Kernel PCA Method'”
   Dimitri Antoniou, Steven D. Schwartz · 2011 · The Journal of Physical Chemistry B
5. Optimizing reaction coordinate by flux maximization in the transition path ensemble
   Li, Wenjin · 2022 · The Journal of Chemical Physics
6. Response theory identifies reaction coordinates and explains critical phenomena in noisy interacting systems
   Niccolò Zagli, Valerio Lucarini, Grigorios A. Pavliotis · 2024 · Journal of Physics A Mathematical and Theoretical
7. How far can we stretch the timescale with RETIS?
   Titus S. van Erp · 2023 · Europhysics Letters (EPL)
8. Minimal Folding Pathways for Coarse-Grained Biopolymer Fragments
   Ali Reza Mohazab, Steven Samuel Plotkin · 2008 · Biophysical Journal
9. Toward a Molecular Theory of Homogeneous Bubble Nucleation: II. Calculation of the Number Density of Critical Nuclei and the Rate of Nucleation
   Korosh Torabi, David S. Corti · 2013 · The Journal of Physical Chemistry B
10. Balancing Accuracy and Cost of Confinement Simulations by Interpolation and Extrapolation of Confinement Energies
    François Villemot, Riccardo Capelli, Giorgio Colombo, Arjan van der Vaart · 2016 · Journal of Chemical Theory and Computation
11. Automated placement of interfaces in conformational kinetics calculations using machine learning
    Gianmarc Grazioli, Carter T. Butts, Ioan Andricioaei · 2017 · The Journal of Chemical Physics
12. Mechanism for the rare fluctuation that powers protein conformational change
    Shanshan Wu, Ao Ma · 2022 · The Journal of Chemical Physics
13. Atomistic simulations of reactive processes in the gas- and condensed-phase
    Pierre‐André Cazade, Jing Huang, Juvenal Yosa, Jarosław J. Szymczak, Markus Meuwly · 2012 · International Reviews in Physical Chemistry
14. Microscopically computing free-energy profiles and transition path time of rare macromolecular transitions
    Pietro Faccioli, Francesco Pederiva · 2012 · Physical Review E
15. A deep learning framework for mesh relaxation in arbitrary Lagrangian-Eulerian simulations
    Ming Feng Jiang, Brian J. Gallagher, Noah Mandell, Alister Maguire, Keith A. Henderson, George F. Weinert · 2019 · SPIE Applications of Machine Learning
16. Equipartition terms in transition path ensemble: Insights from molecular dynamics simulations of alanine dipeptide
    Wenjin Li · 2018 · The Journal of Chemical Physics
17. Unveiling interatomic distances influencing the reaction coordinates in alanine dipeptide isomerization: An explainable deep learning approach
    Kazushi Okada, Takuma Kikutsuji, Kei-ichi Okazaki, Toshifumi Mori, Kang Kim, Nobuyuki Matubayasi · 2024 · The Journal of Chemical Physics
18. Reactive Vortexes in a Naturally Activated Process: Non-Diffusive Rotational Fluxes at Transition State Uncovered by Persistent Homology
    Farid Manuchehrfar, Huiyu Li, Ao Ma, Jie Liang · 2022 · The Journal of Physical Chemistry B
19. Critical comparison of general-purpose collective variables for crystal nucleation
    Julien Lam, Fabio Pietrucci · 2023 · Physical review. E
20. Reaction coordinates and mechanisms
    Baron Peters · 2017 · Elsevier eBooks
21. Using Diffusion Maps to Analyze Reaction Dynamics for a Hydrogen Combustion Benchmark Dataset
    Taehee Ko, Joseph P. Heindel, Xingyi Guan, Teresa L. Head-Gordon, David B. Williams‐Young, Chao Yang · 2023 · Journal of Chemical Theory and Computation
22. Orthogonal order parameters to model the reaction coordinate of an enzyme catalyzed reaction
    Sanjib Paul, Tanmoy Kumar Paul, Srabani Taraphder · 2019 · Journal of Molecular Graphics and Modelling
23. A Mathematical Theory of Optimal Milestoning (with a Detour via Exact Milestoning)
    Ling Lin, Jian-Feng Lu, E. Vanden-Eijnden · 2016 · Communications on Pure and Applied Mathematics
24. Investigating the hyperparameter space of deep neural network models for reaction coordinates
    Kyohei Kawashima, Takumi Sato, Kei-ichi Okazaki, Kang Kim, Nobuyuki Matubayasi, Toshifumi Mori · 2025 · APL Machine Learning
25. Asymmetric Nature of MscL Opening Revealed by Molecular Dynamics Simulations
    Olga N. Rogacheva, Wojciech Kopeć · 2025 · Journal of Chemical Information and Modeling
26. Coupling causality and interpretable machine learning to reveal the reaction coordinate of C–N coupling with a supramolecular Cu-calix[8]arene catalyst
    Radu A. Talmazan, Jakob Gamper, Iván Castillo, Thomas S. Hofer, Maren Podewitz · 2025 · Digital Discovery
27. An Exact Multiple-Time-Step Variational Formulation for the Committor and the Transition Rate
    Chatipat Lorpaiboon, Jonathan Weare, Aaron R. Dinner · 2025 · The Journal of Physical Chemistry B
28. Committors without Descriptors
    Peilin Kang, Jintu Zhang, Enrico Trizio, Tingjun Hou, Michele Parrinello · 2026 · Journal of Chemical Theory and Computation
29. Discriminant analysis optimizes progress coordinate in weighted ensemble simulations of rare event kinetics.
    Praveen Ranganath Prabhakar, Dhiman Ray, I. Andricioaei · 2025 · Journal of Chemical Physics
30. A Deep Learning Method for Computing Committor Functions with Adaptive Sampling
    Bo Lin, Weiqing Ren · 2025 · SIAM Journal on Scientific Computing
31. Structural alignment using the generalized Euclidean distance between conformations
    Ali R. Mohazab, Steven S. Plotkin · 2009 · International Journal of Quantum Chemistry
32. Algorithms for building models of molecular motion from simulations
    Vijay S. Pande, Serafim Batzoglou, Nina Hinrichs · 2007
33. Structural Alignment Using the Generalized Euclidean Distance Between Conformations
    Ali Reza Mohazab, Steven Samuel Plotkin · 2009
34. Survival strategies of artificial active agents
    Luigi Zanovello, Richard J. G. Löffler, Michele Caraglio, Thomas Franosch, Martin Michael Hanczyc, Pietro Faccioli · 2023 · Scientific Reports
35. Mercury’s Chaotic Secular Evolution as a Subdiffusive Process
    Dorian S. Abbot, Robert J. Webber, David M. Hernandez, Sam Hadden, Jonathan Weare · 2024 · The Astrophysical Journal
36. Generative deep-learning reveals collective variables of Fermionic systems
    Raphaël-David Lasseri, David Regnier, Mikaël Frosini, Marc Verrière, Nicolas F. Schunck · 2024 · Physical Review C
37. A Weak Characterization of Slow Variables in Stochastic Dynamical Systems
    Andreas Bittracher, C. Schütte · 2020 · Advances in Dynamics, Optimization and Computation
38. Transitions between secondary structures in isolated polyalanines
    F. Calvo, Pierre Poulain · 2008 · The European Physical Journal D
39. Achieving Reversible Ligand-Protein Unbinding with Deep Learning and Molecular Dynamics through RAVE
    João Marcelo Lamim Ribeiro, Pratyush Tiwary · 2018 · bioRxiv (Cold Spring Harbor Laboratory)
40. Reaction Coordinates are Optimal Channels of Energy Flow
    Ao Ma, Huiyung Li · 2024 · Annual review of physical chemistry (Print)
41. Modeling Changes in Molecular Dynamics Time Series as Wasserstein Barycentric Interpolations
    J. Damjanovic, Yu-Shan Lin, James M. Murphy · 2023 · International Conference on Sampling Theory and Applications
42. Machine learning in molecular biophysics: Protein allostery, multi-level free energy simulations, and lipid phase transitions
    Qiang Cui · 2025 · Biophysics Reviews
43. Heterogeneous nucleation in the random field Ising model
    Liheng Yao, Robert L. Jack · 2023 · The Journal of Chemical Physics
44. Tackling time-reversibility in transition path sampling molecular dynamics simulations
    Dirk Zahn · 2011 · Molecular Simulation
45. Isochronal sampling in non-Boltzmann Monte Carlo methods
    Charlles R. A. Abreu · 2009 · The Journal of Chemical Physics
46. Analysis of DNA deformation patterns in nucleosome core particles based on isometric feature mapping and continuous wavelet transform
    Xi Yang, Hong Yan · 2012 · Chemical Physics Letters
47. Modeling DNA Deformation
    Péter Várnai, Richard Lavery · 2006 · Springer eBooks
48. Time-Lagged Flux in the Transition Path Ensemble: Flux Maximization and Relation to Transition Path Theory
    2022
49. The impact of hydration shell inclusion and chain exclusion in the efficacy of reaction coordinates for homogeneous and heterogeneous ice nucleation
    Kimia Sinaeian, Amir Haji‐Akbari · 2025 · The Journal of Chemical Physics
50. Understanding Mechanisms of Molecular Rare Events from Start to Finish
    Rik S. Breebaart, Gianmarco Lazzeri, Roberto Covino, Peter G. Bolhuis · 2026 · Physical Review Letters
51. Ceci n’est pas un committor, yet it samples like one: Efficient sampling via approximated committor functions
    Enrico Trizio, Giorgia Rossi, Michele Parrinello · 2026 · The Journal of Chemical Physics
52. Transition Path Sampling with Quantum/Classical Mechanics for Reaction Rates
    Frauke Gräter, Wenjin Li · 2014 · Methods in molecular biology
53. The overdamped transmission coefficient: Recovering the true mean first passage time from an inaccurate reaction coordinate
    Ryan D. Yappert, Kartik D Kamat, Baron Peters · 2019 · The Journal of Chemical Physics
54. Trajectory Statistical Learning of the Potential Mean of Force and Diffusion Coefficient from Molecular Dynamics Simulations
    Yi-Tsao Chen, Haw Yang, Jhih‐Wei Chu · 2024 · The Journal of Physical Chemistry B
55. Reactive Processes with Molecular Simulations
    Sabyashachi Mishra, Markus Meuwly · 2010 · Challenges and advances in computational chemistry and physics
56. Network approach to identify the folding transition states of peptides and proteins
    Xuewei Jiang, Anhua Zhong, Changjun Chen, Yanzhao Huang, Yi Xiao · 2012 · Physical Review E
57. New Methods To Find Accurate Reaction Coordinates by Path Sampling
    Gregg T. Beckham, Baron Peters · 2010 · ACS symposium series
58. Committor of elementary reactions on multistate systems
    Péter Király, Dóra Judit Kiss, Gergely Tóth · 2018 · The Journal of Chemical Physics
59. Deep integration of machine learning into computational chemistry and materials science
    Julia Westermayr, Michael Gastegger, Kristof T. Schütt, Reinhard J. Maurer · 2021 · arXiv (Cornell University)
60. Learning collective variables that respect permutational symmetry
    Jiaxin Yuan, Shashank Sule, Yeuk Yin Lam, Maria Cameron · 2025 · The Journal of Chemical Physics
61. Using Time Dependent Rate Analysis to Evaluate the Quality of Machine Learned Reaction Coordinates for Biasing and Computing Kinetics
    Nicodemo Mazzaferro, Suemin Lee, Pilar Cossio, Pratyush Tiwary, Glen M. Hocky · 2025 · The Journal of Physical Chemistry B
62. Deep learning of committor for ion dissociation and interpretable analysis of solvent effects using atom-centered symmetry functions
    Kenji Okada, Kazushi Okada, Kei-ichi Okazaki, Toshifumi Mori, Kang Kim, Nobuyuki Matubayasi · 2026 · The Journal of Chemical Physics
63. Designing transferable transition state guided collective variables via interpretable machine learning models for enhanced sampling: a case study on polymer collapse transition
    Saikat Dhibar, Biman Jana · 2026 · Physical Chemistry Chemical Physics
64. Improving individual committor estimates and data efficiency in reaction coordinate tests with the empirical Bayes method
    Akshay Gurumoorthi, Baron Peters · 2026 · The Journal of Chemical Physics
65. Roadmap on novel computational approaches for bridging length and time scales: addressing challenges in modeling processes, characterization, and performance of metals and alloys
    Abigail Hunter, Vinamra Agrawal, Irene J. Beyerlein, Somnath Ghosh, Caglar Oskay, Boyang Gu, Youping Chen, Stephen Caleb Foster, Justin W. Wilkerson, Xingsheng Sun et al. · 2026 · Modelling and Simulation in Materials Science and Engineering
66. Collective variable design for biomolecular conformational dynamics.
    Darko Mitrovic, Adrien Schahl, A. Marciniak, L. Delemotte · 2026 · Current Opinion in Structural Biology
67. Pathway-resolved observable memory reveals hidden mediation from sparse conformational measurements.
    Q. Cui · 2026 · Journal of Chemical Physics
68. Spatial Averaging: Sampling Enhancement for Exploring Configurational Space of Atomic Clusters and Biomolecules
    Florent Hédin, Nuria Plattner, Jimmie D. Doll, Markus Meuwly · 2014 · Journal of Chemical Theory and Computation
69. Modeling martensic transformations in crystalline solids: validity and redesign of geometric approaches
    Dirk Zahn · 2011 · Zeitschrift für Kristallographie
70. From high-dimensional committors to reactive insights
    Nils E. Strand, Schuyler B. Nicholson, Hadrien Vroylandt, Todd R. Gingrich · 2024 · The Journal of Chemical Physics
71. Energy Decomposition along Reaction Coordinate: Theory and Applications to Nonequilibrium Ensembles of Trajectories
    Wenjin Li · 2022 · The Journal of Physical Chemistry A
72. Molecular dynamics and ESR spectra of a nitroxide spin label at solvent-exposed surface sites in proteins
    Deniz Sezer · 2007 · eCommons (Cornell University)
73. Machine learning approaches for analyzing and enhancing molecular dynamics simulations
    Yihang Wang, João Marcelo Lamim Ribeiro, Pratyush Tiwary · 2019 · arXiv (Cornell University)
74. Dynamics of activation in the voltage-sensing domain of Ci-VSP
    Spencer C. Guo, Rong Shen, Benoı̂t Roux, Aaron R. Dinner · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
75. Point-set manifold processing for computational mechanics: thin shells, reduced order modeling, cell motility and molecular conformations
    Daniel Millán · 2012
76. Simplified models for simulating replica exchange simulations and recovering kinetics of protein folding
    Weihua Zheng · 2009
77. Analysis of molecular motion using non-linear dimensionality reduction
    Hernán Stamati · 2007 · Rice Research Repository (Rice University)
78. Atomistic Simulations of Reactions and Transition States
    Markus Meuwly · 2008 · WORLD SCIENTIFIC eBooks
79. Mechanistic applications of volume profiles for chemical and biochemical processes
    Heather A. Wiebe · 2018 · Summit (Simon Fraser University)
80. Competitive Nucleation in Nanoclusters
    Cletus C. Asuquo · 2015 · HARVEST (University of Saskatchewan)
81. A novel mechanism for energy activation in biomolecules
    Shanshan Wu, Ao Ma · 2020 · arXiv (Cornell University)
82. Exact Topology of Dynamic Probability Surface of an Activated Process by Persistent Homology
    Farid Manuchehrfar, Huiyu Li, Tian, Wei, Ao Ma, Jie Liang · 2021 · arXiv (Cornell University)
83. Force-Correction Analysis Method for Derivation of Multidimensional Free Energy Landscapes from Adaptively Biased Replica Simulations
    Fabrizio Marinelli, José D. Faraldo‐Gómez · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
84. Reaction coordinates by nonlinear dimensionality reduction
    Zhen Zhang, Yao Kun Lei, Jun Zhang, Yi Qin Gao · 2021 · Chinese Journal of Chemical Physics
85. Uncovering One-Dimensional Reaction Coordinate that Underlies Structure-Function Relationship of Proteins
    Shanshan Wu, Huiyu Li, Ao Ma · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
86. From evaluating the performance of approximations in Density Functional Theory to a Machine Learning design
    Pedram Tavazohi · 2022
87. Potential Energy Weighted Reactive Flux and Total Rate of Change of Potential Energy: Theory and Illustrative Applications
    2022
88. In silico approaches to biomacromolecules through conformational dynamics and catalysis
    Divya Rai, Satyajit Khatua, Tanmoy Kumar Paul, Srabani Taraphder · 2023 · Elsevier eBooks
89. Information Thermodynamics of Transition Paths
    Miranda Louwerse · 2023 · Springer theses
90. Conclusions
    Miranda Louwerse · 2023 · Springer theses
91. Variational analysis and AI algorithm implementation of free energy landscapes of molecular system
    Bochuan Du, Pu Tian · 2024 · Acta Physica Sinica
92. Analysis of the Dynamics of a Complex, Multipathway Reaction: Insulin Dimer Dissociation
    Kwanghoon Jeong, Spencer C. Guo, Sammy Allaw, Aaron R. Dinner · 2024 · The Journal of Physical Chemistry B
93. Machine Learning of Slow Collective Variables and Enhanced Sampling via Spatial Techniques
    Tuğçe Gökdemir, Jakub Rydzewski · 2025 · Qeios
94. Quantum Monte Carlo simulations
    Hyeonseong Jung, Shiho Kim · 2025 · Advances in computers
95. Deep learning of committor and explainable artificial intelligence analysis for identifying reaction coordinates
    Toshifumi Mori, Kei-ichi Okazaki, Kang Kim, Nobuyuki Matubayasi · 2026 · Chemical Physics Reviews
96. Machine Learning Methods for Molecular Dynamic Simulations
    Zineb Belkacemi · 2022
97. Prebiotic chemistry kinetics from stochastic sampling (PROCESS)
    Léon Huet · 2024
98. Tripeptide dynamics from empirical and machine-learned energy functions
    S. Aydın, Valerii Andreichev, Pantelis Maragkoudakis, Markus Meuwly · 2025 · Biophysical Journal
99. Hierarchical geometric deep learning enables scalable analysis of molecular dynamics
    Zihan Pengmei, Spencer C. Guo, Chatipat Lorpaiboon, Aaron R. Dinner · 2026 · The Journal of Chemical Physics
100. A continuous-space analytical framework for committor functions from molecular dynamics
     Siqin Cao, Xuhui Huang · 2026 · The Journal of Chemical Physics