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Variational Approach to Molecular Kinetics
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Outgoing claims: the papers this work cites, builds on, or argues with.
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LINCS: A linear constraint solver for molecular simulations
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Kinetic analysis of molecular dynamics simulations reveals changes in the denatured state and switch of folding pathways upon single‐point mutation of a β‐sheet miniprotein
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Essential dynamics of reversible peptide folding: memory-free conformational dynamics governed by internal hydrogen bonds
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Towards a Theory of Transition Paths
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Markov models and dynamical fingerprints: Unraveling the complexity of molecular kinetics
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The Protein Folding Network
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Robust Perron cluster analysis in conformation dynamics
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Transition networks for modeling the kinetics of conformational change in macromolecules
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Everything you wanted to know about Markov State Models but were afraid to ask
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Identification of almost invariant aggregates in reversible nearly uncoupled Markov chains
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Statistical clustering techniques for the analysis of long molecular dynamics trajectories: analysis of 2.2-ns trajectories of YPGDV
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Extracting Markov Models of Peptide Conformational Dynamics from Simulation Data
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Transition Networks for the Comprehensive Characterization of Complex Conformational Change in Proteins
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An Analysis of the Validity of Markov State Models for Emulating the Dynamics of Classical Molecular Systems and Ensembles
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MSMBuilder2: Modeling Conformational Dynamics on the Picosecond to Millisecond Scale
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Improvements in Markov State Model Construction Reveal Many Non-Native Interactions in the Folding of NTL9
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Relationship between Side Chain Structure and 14-Helix Stability of β3-Peptides in Water
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Markov State Model Reveals Folding and Functional Dynamics in Ultra-Long MD Trajectories
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Describing Protein Folding Kinetics by Molecular Dynamics Simulations. 1. Theory
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Coarse Master Equations for Peptide Folding Dynamics
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Error analysis and efficient sampling in Markovian state models for molecular dynamics
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A coarse graining method for the identification of transition rates between molecular conformations
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Canonical sampling through velocity rescaling
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Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics
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Hierarchical analysis of conformational dynamics in biomolecules: Transition networks of metastable states
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Dihedral angle principal component analysis of molecular dynamics simulations
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Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory
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Probability distributions of molecular observables computed from Markov models
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Probability distributions of molecular observables computed from Markov models. II. Uncertainties in observables and their time-evolution
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Identification of metastable states in peptide’s dynamics
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A Bayesian method for construction of Markov models to describe dynamics on various time-scales
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Adaptive Spectral Clustering for Conformation Analysis
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Markov models of molecular kinetics: Generation and validation
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Markov state models based on milestoning
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Dynamic neutron scattering from conformational dynamics. I. Theory and Markov models
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Dynamic neutron scattering from conformational dynamics. II. Application using molecular dynamics simulation and Markov modeling
inferredcites →https://doi.org/10.1073/pnas.0406234101openalex-snapshot
Hidden complexity of free energy surfaces for peptide (protein) folding
inferredcites →https://doi.org/10.1073/pnas.0605580103openalex-snapshot
Understanding ensemble protein folding at atomic detail
inferredcites →https://doi.org/10.1073/pnas.0905466106openalex-snapshot
Constructing the equilibrium ensemble of folding pathways from short off-equilibrium simulations
inferredcites →https://doi.org/10.1073/pnas.1003962107openalex-snapshot
Protein folded states are kinetic hubs
inferredcites →https://doi.org/10.1073/pnas.1004646108openalex-snapshot
Dynamical fingerprints for probing individual relaxation processes in biomolecular dynamics with simulations and kinetic experiments
inferredcites →https://doi.org/10.1073/pnas.1103547108openalex-snapshot
Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations
inferredcites →https://doi.org/10.1073/pnas.1201810109openalex-snapshot
Simple few-state models reveal hidden complexity in protein folding
inferredcites →https://doi.org/10.1073/pnas.1210983109openalex-snapshot
Kinetic characterization of the critical step in HIV-1 protease maturation
inferredcites →https://doi.org/10.1126/science.1187409openalex-snapshot
Atomic-Level Characterization of the Structural Dynamics of Proteins
inferredcites →https://doi.org/10.1126/science.1208351openalex-snapshot
How Fast-Folding Proteins Fold
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On the Approximation Quality of Markov State Models
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A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems
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The Many Proofs and Applications of Perron’s Theorem
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Kinesin Assembly and Movement in Cells
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Ribosome Structure and Dynamics During Translocation and Termination
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Statistical error estimation and grid-free hierarchical refinement in conformation dynamics
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Hierarchical Time-Lagged Independent Component Analysis: Computing Slow Modes and Reaction Coordinates for Large Molecular Systems
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Commute Maps: Separating Slowly Mixing Molecular Configurations for Kinetic Modeling
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A Maximum-Caliber Approach to Predicting Perturbed Folding Kinetics Due to Mutations
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Ward Clustering Improves Cross-Validated Markov State Models of Protein Folding
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Adaptive Tensor Train Metadynamics for High-Dimensional Free Energy Exploration
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tICA-Metadynamics: Accelerating Metadynamics by Using Kinetically Selected Collective Variables
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Recognizing Local and Global Structural Motifs at the Atomic Scale
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A Minimum Variance Clustering Approach Produces Robust and Interpretable Coarse-Grained Models
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Predicting the Conformational Variability of Abl Tyrosine Kinase using Molecular Dynamics Simulations and Markov State Models
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Transferable Neural Networks for Enhanced Sampling of Protein Dynamics
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Rapid Calculation of Molecular Kinetics Using Compressed Sensing
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Protein Folding Free Energy Landscape along the Committor - the Optimal Folding Coordinate
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String Method with Swarms-of-Trajectories, Mean Drifts, Lag Time, and Committor
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Temporally Coherent Backmapping of Molecular Trajectories From Coarse-Grained to Atomistic Resolution
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Girsanov Reweighting Enhanced Sampling Technique (GREST): On-the-Fly Data-Driven Discovery of and Enhanced Sampling in Slow Collective Variables
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Molecular Latent Space Simulators for Distributed and Multimolecular Trajectories
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Tutorial on Molecular Latent Space Simulators (LSSs): Spatially and Temporally Continuous Data-Driven Surrogate Dynamical Models of Molecular Systems
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Integrated Variational Approach to Conformational Dynamics: A Robust Strategy for Identifying Eigenfunctions of Dynamical Operators
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Analyzing the Long Time-Scale Dynamics of Uremic Toxins Bound to Sudlow Site II in Human Serum Albumin
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Conformational Fluctuations in β2-Microglubulin Using Markov State Modeling and Molecular Dynamics
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Deep-Learning-Assisted Enhanced Sampling for Exploring Molecular Conformational Changes
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Analyzing Multimodal Probability Measures with Autoencoders
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Implementation of Girsanov Reweighting in OpenMM and Deeptime
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Computational Analysis of the Fully Activated Orexin Receptor 2 across Various Thermodynamic Ensembles with Surface Tension Monitoring and Markov State Modeling
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Imaging Metastable States and Transitions in Proteins by Trajectory Map
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Predicting Optimal DEER Label Positions to Study Protein Conformational Heterogeneity
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Transfer Learning from Markov Models Leads to Efficient Sampling of Related Systems
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Maximizing Kinetic Information Gain of Markov State Models for Optimal Design of Spectroscopy Experiments
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Recovery of Protein Folding Funnels from Single-Molecule Time Series by Delay Embeddings and Manifold Learning
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High-Resolution Markov State Models for the Dynamics of Trp-Cage Miniprotein Constructed Over Slow Folding Modes Identified by State-Free Reversible VAMPnets
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Kinetics of Molecular Diffusion and Self-Assembly: Glycine on Cu{110}
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Fast Functionalization with High Performance in the Autonomous Information Engine
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Toward a Benchmark for Markov State Models: The Folding of HP35
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Unbiasing Enhanced Sampling on a High-Dimensional Free Energy Surface with a Deep Generative Model
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Understanding the Fast-Triggering Unfolding Dynamics of FK-11 upon Photoexcitation of Azobenzene
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Slicing and Dicing: Optimal Coarse-Grained Representation to Preserve Molecular Kinetics
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The Isomeric Preference of an Atypical Dopamine Transporter Inhibitor Contributes to Its Selection of the Transporter Conformation
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Automatic State Partitioning for Multibody Systems (APM): An Efficient Algorithm for Constructing Markov State Models To Elucidate Conformational Dynamics of Multibody Systems
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Modeling Molecular Kinetics with tICA and the Kernel Trick
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Conserve Water: A Method for the Analysis of Solvent in Molecular Dynamics
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Memory Unlocks the Future of Biomolecular Dynamics: Transformative Tools to Uncover Physical Insights Accurately and Efficiently
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Markov State Models: From an Art to a Science
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Microsecond Dynamics of the Pyrophosphate Ion Release in SARS-CoV-2 RNA Polymerase
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Optimal Dimensionality Reduction of Multistate Kinetic and Markov-State Models
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Molecular dynamics simulations reveal ligand-controlled positioning of a peripheral protein complex in membranes
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VAMPnets for deep learning of molecular kinetics
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Deep learning for universal linear embeddings of nonlinear dynamics
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Millisecond dynamics of BTK reveal kinome-wide conformational plasticity within the apo kinase domain
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DeepGreen: deep learning of Green’s functions for nonlinear boundary value problems
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Predicting efficacy of drug-carrier nanoparticle designs for cancer treatment: a machine learning-based solution
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Ligand-bound glutamine binding protein assumes multiple metastable binding sites with different binding affinities
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Generative learning for nonlinear dynamics
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Promising directions of machine learning for partial differential equations
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Advancements in characterization of protein dynamics with machine learning
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Markov models of the apo-MDM2 lid region reveal diffuse yet two-state binding dynamics and receptor poses for computational docking
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Role of conformational dynamics in the evolution of novel enzyme function
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Learning the reaction coordinate: collective variables from physical intuition to generative models
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Integration of machine learning with computational structural biology of plants
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Computational methods for exploring protein conformations
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Perspective: Markov models for long-timescale biomolecular dynamics
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Gaussian Markov transition models of molecular kinetics
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Variational cross-validation of slow dynamical modes in molecular kinetics
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Projected metastable Markov processes and their estimation with observable operator models
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Estimation and uncertainty of reversible Markov models
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Nonparametric variational optimization of reaction coordinates
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Variational tensor approach for approximating the rare-event kinetics of macromolecular systems
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Communication: Consistent interpretation of molecular simulation kinetics using Markov state models biased with external information
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Diffusion Monte Carlo study on temporal evolution of entropy and free energy in nonequilibrium processes
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Dimensional reduction of Markov state models from renormalization group theory
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Density-based cluster algorithms for the identification of core sets
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Optimized parameter selection reveals trends in Markov state models for protein folding
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Identification of simple reaction coordinates from complex dynamics
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Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias
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Set-free Markov state model building
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Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations
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Girsanov reweighting for path ensembles and Markov state models
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Path lumping: An efficient algorithm to identify metastable path channels for conformational dynamics of multi-body systems
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A variational conformational dynamics approach to the selection of collective variables in metadynamics
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Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics
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MSM/RD: Coupling Markov state models of molecular kinetics with reaction-diffusion simulations
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Collective variable discovery and enhanced sampling using autoencoders: Innovations in network architecture and error function design
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Conformational analysis of replica exchange MD: Temperature-dependent Markov networks for FF amyloid peptides
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Girsanov reweighting for metadynamics simulations
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Assessment and optimization of collective variables for protein conformational landscape: GB1 β -hairpin as a case study
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From metastable to coherent sets— Time-discretization schemes
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A kernel-based approach to molecular conformation analysis
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Galerkin approximation of dynamical quantities using trajectory data
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Multi-dimensional spectral gap optimization of order parameters (SGOOP) through conditional probability factorization
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Variational selection of features for molecular kinetics
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