Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

TweTriS: Twenty trillion-atom simulation

(2019) Nikola Tchipev et al.   INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS

Unmasking Clever Hans predictors and assessing what machines really learn

(2019) Sebastian Lapuschkin et al.   Nature Communications

Recent advances in machine learning towards multiscale soft materials design

(2019) Nicholas E Jackson et al.   Current Opinion in Chemical Engineering

Nonlinear discovery of slow molecular modes using state-free reversible VAMPnets

(2019) Wei Chen et al.   JOURNAL OF CHEMICAL PHYSICS

Koopman operator-based model reduction for switched-system control of PDEs

(2019) Sebastian Peitz et al.   AUTOMATICA

Deflation reveals dynamical structure in nondominant reaction coordinates

(2019) Brooke E. Husic et al.   JOURNAL OF CHEMICAL PHYSICS

Enhanced sampling in molecular dynamics

(2019) Yi Isaac Yang et al.   JOURNAL OF CHEMICAL PHYSICS

Capabilities and limitations of time-lagged autoencoders for slow mode discovery in dynamical systems

(2019) Wei Chen et al.   JOURNAL OF CHEMICAL PHYSICS

High-Resolution Markov State Models for the Dynamics of Trp-Cage Miniprotein Constructed Over Slow Folding Modes Identified by State-Free Reversible VAMPnets

(2019) Hythem Sidky et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning

(2019) Frank Noé et al.   SCIENCE

Adaptive enhanced sampling by force-biasing using neural networks

(2018) Ashley Z. Guo et al.   JOURNAL OF CHEMICAL PHYSICS

Reweighted autoencoded variational Bayes for enhanced sampling (RAVE)

(2018) João Marcelo Lamim Ribeiro et al.   JOURNAL OF CHEMICAL PHYSICS

Learning free energy landscapes using artificial neural networks

(2018) Hythem Sidky et al.   JOURNAL OF CHEMICAL PHYSICS

SchNet – A deep learning architecture for molecules and materials

(2018) K. T. Schütt et al.   JOURNAL OF CHEMICAL PHYSICS

Collective variable discovery and enhanced sampling using autoencoders: Innovations in network architecture and error function design

(2018) Wei Chen et al.   JOURNAL OF CHEMICAL PHYSICS

Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics

(2018) Christoph Wehmeyer et al.   JOURNAL OF CHEMICAL PHYSICS

Transferable Neural Networks for Enhanced Sampling of Protein Dynamics

(2018) Mohammad M. Sultan et al.   Journal of Chemical Theory and Computation

Data-Driven Model Reduction and Transfer Operator Approximation

(2018) Stefan Klus et al.   JOURNAL OF NONLINEAR SCIENCE

Collective Variables from Local Fluctuations

(2018) Dan Mendels et al.   Journal of Physical Chemistry Letters

Markov State Models: From an Art to a Science

(2018) Brooke E. Husic et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

A Study of the Morphology, Dynamics, and Folding Pathways of Ring Polymers with Supramolecular Topological Constraints Using Molecular Simulation and Nonlinear Manifold Learning

(2018) Jiang Wang et al.   MACROMOLECULES

Tensor-based dynamic mode decomposition

(2018) Stefan Klus et al.   NONLINEARITY

An Automatic Adaptive Importance Sampling Algorithm for Molecular Dynamics in Reaction Coordinates

(2018) J. Quer et al.   SIAM JOURNAL ON SCIENTIFIC COMPUTING

VAMPnets for deep learning of molecular kinetics

(2018) Andreas Mardt et al.   Nature Communications

NSF’s Inaugural Software Institutes: The Science Gateways Community Institute and the Molecular Sciences Software Institute

(2018) Nancy Wilkins-Diehr et al.   COMPUTING IN SCIENCE & ENGINEERING

Girsanov reweighting for metadynamics simulations

(2018) Luca Donati et al.   JOURNAL OF CHEMICAL PHYSICS

Automated design of collective variables using supervised machine learning

(2018) Mohammad M. Sultan et al.   JOURNAL OF CHEMICAL PHYSICS

Metadynamics with Discriminants: A Tool for Understanding Chemistry

(2018) GiovanniMaria Piccini et al.   Journal of Chemical Theory and Computation

Machine learning for molecular and materials science

(2018) Keith T. Butler et al.   NATURE

ACS Central Science Virtual Issue on Machine Learning

(2018) Andrew L. Ferguson   ACS Central Science

Deep clustering of protein folding simulations

(2018) Debsindhu Bhowmik et al.   BMC BIOINFORMATICS

Folding a small protein using harmonic linear discriminant analysis

(2018) Dan Mendels et al.   JOURNAL OF CHEMICAL PHYSICS

Perspective: Computational chemistry software and its advancement as illustrated through three grand challenge cases for molecular science

(2018) Anna Krylov et al.   JOURNAL OF CHEMICAL PHYSICS

Toward Achieving Efficient and Accurate Ligand-Protein Unbinding with Deep Learning and Molecular Dynamics through RAVE

(2018) João Marcelo Lamim Ribeiro et al.   Journal of Chemical Theory and Computation

PotentialNet for Molecular Property Prediction

(2018) Evan N. Feinberg et al.   ACS Central Science

A variational conformational dynamics approach to the selection of collective variables in metadynamics

(2017) James McCarty et al.   JOURNAL OF CHEMICAL PHYSICS

Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations

(2017) Hao Wu et al.   JOURNAL OF CHEMICAL PHYSICS

Girsanov reweighting for path ensembles and Markov state models

(2017) L. Donati et al.   JOURNAL OF CHEMICAL PHYSICS

Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias

(2017) Feliks Nüske et al.   JOURNAL OF CHEMICAL PHYSICS

tICA-Metadynamics: Accelerating Metadynamics by Using Kinetically Selected Collective Variables

(2017) Mohammad M. Sultan et al.   Journal of Chemical Theory and Computation

Neural Network and Nearest Neighbor Algorithms for Enhancing Sampling of Molecular Dynamics

(2017) Raimondas Galvelis et al.   Journal of Chemical Theory and Computation

BayesWHAM: A Bayesian approach for free energy estimation, reweighting, and uncertainty quantification in the weighted histogram analysis method

(2017) Andrew L. Ferguson   JOURNAL OF COMPUTATIONAL CHEMISTRY

On Convergence of Extended Dynamic Mode Decomposition to the Koopman Operator

(2017) Milan Korda et al.   JOURNAL OF NONLINEAR SCIENCE

Nonlinear machine learning in simulations of soft and biological materials

(2017) J. Wang et al.   MOLECULAR SIMULATION

Stochastic Neural Network Approach for Learning High-Dimensional Free Energy Surfaces

(2017) Elia Schneider et al.   PHYSICAL REVIEW LETTERS

Intrinsic map dynamics exploration for uncharted effective free-energy landscapes

(2017) Eliodoro Chiavazzo et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

De-biasing the dynamic mode decomposition for applied Koopman spectral analysis of noisy datasets

(2017) Maziar S. Hemati et al.   THEORETICAL AND COMPUTATIONAL FLUID DYNAMICS

Landmark diffusion maps (L-dMaps): Accelerated manifold learning out-of-sample extension

(2017) Andrew W. Long et al.   APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

Enhancing Important Fluctuations: Rare Events and Metadynamics from a Conceptual Viewpoint

(2016) Omar Valsson et al.   Annual Review of Physical Chemistry

Charting molecular free-energy landscapes with an atlas of collective variables

(2016) Behrooz Hashemian et al.   JOURNAL OF CHEMICAL PHYSICS

Hierarchical Time-Lagged Independent Component Analysis: Computing Slow Modes and Reaction Coordinates for Large Molecular Systems

(2016) Guillermo Pérez-Hernández et al.   Journal of Chemical Theory and Computation

Commute Maps: Separating Slowly Mixing Molecular Configurations for Kinetic Modeling

(2016) Frank Noé et al.   Journal of Chemical Theory and Computation

Unconstrained enhanced sampling for free energy calculations of biomolecules: a review

(2016) Yinglong Miao et al.   MOLECULAR SIMULATION

Multiensemble Markov models of molecular thermodynamics and kinetics

(2016) Hao Wu et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Spectral gap optimization of order parameters for sampling complex molecular systems

(2016) Pratyush Tiwary et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Dynamic Mode Decomposition with Control

(2016) Joshua L. Proctor et al.   SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS

Multiresolution Dynamic Mode Decomposition

(2016) J. Nathan Kutz et al.   SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS

Beating the Millisecond Barrier in Molecular Dynamics Simulations

(2015) Frank Noé   BIOPHYSICAL JOURNAL

Machine learning of single molecule free energy surfaces and the impact of chemistry and environment upon structure and dynamics

(2015) Rachael A. Mansbach et al.   JOURNAL OF CHEMICAL PHYSICS

Systematic characterization of protein folding pathways using diffusion maps: Application to Trp-cage miniprotein

(2015) Sang Beom Kim et al.   JOURNAL OF CHEMICAL PHYSICS

Modeling Molecular Kinetics with tICA and the Kernel Trick

(2015) Christian R. Schwantes et al.   Journal of Chemical Theory and Computation

Kinetic Distance and Kinetic Maps from Molecular Dynamics Simulation

(2015) Frank Noé et al.   Journal of Chemical Theory and Computation

A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition

(2015) Matthew O. Williams et al.   JOURNAL OF NONLINEAR SCIENCE

Molecular Dynamics with On-the-Fly Machine Learning of Quantum-Mechanical Forces

(2015) Zhenwei Li et al.   PHYSICAL REVIEW LETTERS

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

(2015) Sebastian Bach et al.   PLoS One

Markov state models of biomolecular conformational dynamics

(2014) John D Chodera et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Variational Approach to Molecular Kinetics

(2014) Feliks Nüske et al.   Journal of Chemical Theory and Computation

Nonlinear Machine Learning of Patchy Colloid Self-Assembly Pathways and Mechanisms

(2014) Andrew W. Long et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Fast recovery of free energy landscapes via diffusion-map-directed molecular dynamics

(2014) Jordane Preto et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Dynamic mode decomposition for large and streaming datasets

(2014) Maziar S. Hemati et al.   PHYSICS OF FLUIDS

A Computational Method to Extract Macroscopic Variables and Their Dynamics in Multiscale Systems

(2014) Gary Froyland et al.   SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS

Reduced Models in Chemical Kinetics via Nonlinear Data-Mining

(2014) Eliodoro Chiavazzo et al.   Processes

Discovering Mountain Passes via Torchlight: Methods for the Definition of Reaction Coordinates and Pathways in Complex Macromolecular Reactions

(2013) Mary A. Rohrdanz et al.   Annual Review of Physical Chemistry

Enhanced Sampling in Molecular Dynamics Using Metadynamics, Replica-Exchange, and Temperature-Acceleration

(2013) Cameron Abrams et al.   Entropy

Modeling and enhanced sampling of molecular systems with smooth and nonlinear data-driven collective variables

(2013) Behrooz Hashemian et al.   JOURNAL OF CHEMICAL PHYSICS

Identification of slow molecular order parameters for Markov model construction

(2013) Guillermo Pérez-Hernández et al.   JOURNAL OF CHEMICAL PHYSICS

Improvements in Markov State Model Construction Reveal Many Non-Native Interactions in the Folding of NTL9

(2013) Christian R. Schwantes et al.   Journal of Chemical Theory and Computation

Demonstrating the Transferability and the Descriptive Power of Sketch-Map

(2013) Michele Ceriotti et al.   Journal of Chemical Theory and Computation

Rapid Exploration of Configuration Space with Diffusion-Map-Directed Molecular Dynamics

(2013) Wenwei Zheng et al.   JOURNAL OF PHYSICAL CHEMISTRY B

A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems

(2013) Frank Noé et al.   MULTISCALE MODELING & SIMULATION

Time-Scale Separation from Diffusion-Mapped Delay Coordinates

(2013) T. Berry et al.   SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS

Protein folding and de novo protein design for biotechnological applications

(2013) George A. Khoury et al.   TRENDS IN BIOTECHNOLOGY

Fuzzy spectral clustering by PCCA+: application to Markov state models and data classification

(2013) Susanna Röblitz et al.   Advances in Data Analysis and Classification

On the Use of Experimental Observations to Bias Simulated Ensembles

(2012) Jed W. Pitera et al.   Journal of Chemical Theory and Computation

Variants of Dynamic Mode Decomposition: Boundary Condition, Koopman, and Fourier Analyses

(2012) Kevin K. Chen et al.   JOURNAL OF NONLINEAR SCIENCE

Using sketch-map coordinates to analyze and bias molecular dynamics simulations

(2012) G. A. Tribello et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

The Protein-Folding Problem, 50 Years On

(2012) K. A. Dill et al.   SCIENCE

Density of States–Based Molecular Simulations

(2012) Sadanand Singh et al.   Annual Review of Chemical and Biomolecular Engineering

Nonlinear dimensionality reduction in molecular simulation: The diffusion map approach

(2011) Andrew L. Ferguson et al.   CHEMICAL PHYSICS LETTERS

Integrating diffusion maps with umbrella sampling: Application to alanine dipeptide

(2011) Andrew L. Ferguson et al.   JOURNAL OF CHEMICAL PHYSICS

Dynamical reweighting: Improved estimates of dynamical properties from simulations at multiple temperatures

(2011) John D. Chodera et al.   JOURNAL OF CHEMICAL PHYSICS

Optimal use of data in parallel tempering simulations for the construction of discrete-state Markov models of biomolecular dynamics

(2011) Jan-Hendrik Prinz et al.   JOURNAL OF CHEMICAL PHYSICS

Determination of reaction coordinates via locally scaled diffusion map

(2011) Mary A. Rohrdanz et al.   JOURNAL OF CHEMICAL PHYSICS

Markov models of molecular kinetics: Generation and validation

(2011) Jan-Hendrik Prinz et al.   JOURNAL OF CHEMICAL PHYSICS

Simplifying the representation of complex free-energy landscapes using sketch-map

(2011) Michele Ceriotti et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

How Fast-Folding Proteins Fold

(2011) K. Lindorff-Larsen et al.   SCIENCE

Metadynamics

(2011) Alessandro Barducci et al.   Wiley Interdisciplinary Reviews-Computational Molecular Science

The reweighted path ensemble

(2010) Jutta Rogal et al.   JOURNAL OF CHEMICAL PHYSICS

Everything you wanted to know about Markov State Models but were afraid to ask

(2010) Vijay S. Pande et al.   METHODS

Graphite-diamond phase coexistence study employing a neural-network mapping of theab initiopotential energy surface

(2010) Rustam Z. Khaliullin et al.   PHYSICAL REVIEW B

Systematic determination of order parameters for chain dynamics using diffusion maps

(2010) A. L. Ferguson et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

A self-learning algorithm for biased molecular dynamics

(2010) Gareth A. Tribello et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Atomic-Level Characterization of the Structural Dynamics of Proteins

(2010) D. E. Shaw et al.   SCIENCE

Design of therapeutic proteins with enhanced stability

(2009) N. Chennamsetty et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Discovery Through the Computational Microscope

(2009) Eric H. Lee et al.   STRUCTURE

The Protein Folding Problem

(2008) Ken A. Dill et al.   Annual Review of Biophysics

Graph Laplacian Tomography From Unknown Random Projections

(2008) R.R. Coifman et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Adaptive biasing force method for scalar and vector free energy calculations

(2008) Eric Darve et al.   JOURNAL OF CHEMICAL PHYSICS

Metadynamics: a method to simulate rare events and reconstruct the free energy in biophysics, chemistry and material science

(2008) Alessandro Laio et al.   REPORTS ON PROGRESS IN PHYSICS