Temporally Coherent Backmapping of Molecular Trajectories From Coarse-Grained to Atomistic Resolution

E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

(2022) Simon Batzner et al.   Nature Communications

Adversarial reverse mapping of condensed-phase molecular structures: Chemical transferability

(2021) Marc Stieffenhofer et al.   APL Materials

Machine learning implicit solvation for molecular dynamics

(2021) Yaoyi Chen et al.   JOURNAL OF CHEMICAL PHYSICS

Deep learning the slow modes for rare events sampling

(2021) Luigi Bonati et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

(2020) Kirill Shmilovich et al.   JOURNAL OF PHYSICAL CHEMISTRY B

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

(2020) Hythem Sidky et al.   MOLECULAR PHYSICS

Backmapping coarse-grained macromolecules: An efficient and versatile machine learning approach

(2020) Wei Li et al.   JOURNAL OF CHEMICAL PHYSICS

Large-scale simulation of biomembranes incorporating realistic kinetics into coarse-grained models

(2020) Mohsen Sadeghi et al.   Nature Communications

Reconstruction of protein structures from single-molecule time series

(2020) Maximilian Topel et al.   JOURNAL OF CHEMICAL PHYSICS

Coarse graining molecular dynamics with graph neural networks

(2020) Brooke E. Husic et al.   JOURNAL OF CHEMICAL PHYSICS

Machine Learning of Coarse-Grained Molecular Dynamics Force Fields

(2019) Jiang Wang et al.   ACS Central Science

Variational Approach for Learning Markov Processes from Time Series Data

(2019) Hao Wu et al.   JOURNAL OF NONLINEAR SCIENCE

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

(2019) Frank Noé et al.   SCIENCE

A data ecosystem to support machine learning in materials science

(2019) Ben Blaiszik et al.   MRS Communications

Coarse-graining auto-encoders for molecular dynamics

(2019) Wujie Wang et al.   npj Computational Materials

Reweighted autoencoded variational Bayes for enhanced sampling (RAVE)

(2018) João Marcelo Lamim Ribeiro 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

Coarse-Grained Molecular Simulation and Nonlinear Manifold Learning of Archipelago Asphaltene Aggregation and Folding

(2018) Jiang Wang et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Deep Learning for Computer Vision: A Brief Review

(2018) Athanasios Voulodimos et al.   Computational Intelligence and Neuroscience

Automated design of collective variables using supervised machine learning

(2018) Mohammad M. Sultan 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

Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

(2017) Waseem Rawat et al.   NEURAL COMPUTATION

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

OpenMM 7: Rapid development of high performance algorithms for molecular dynamics

(2017) Peter Eastman et al.   PLoS Computational Biology

The Materials Data Facility: Data Services to Advance Materials Science Research

(2016) B. Blaiszik et al.   JOM

Enhanced sampling techniques in molecular dynamics simulations of biological systems

(2015) Rafael C. Bernardi et al.   BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS

Dynamic properties of force fields

(2015) F. Vitalini et al.   JOURNAL OF CHEMICAL PHYSICS

Estimation and uncertainty of reversible Markov models

(2015) Benjamin Trendelkamp-Schroer et al.   JOURNAL OF CHEMICAL PHYSICS

Kinetic Distance and Kinetic Maps from Molecular Dynamics Simulation

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

PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models

(2015) Martin K. Scherer et al.   Journal of Chemical Theory and Computation

Molecular simulations and visualization: introduction and overview

(2014) Jonathan D. Hirst et al.   FARADAY DISCUSSIONS

Variational Approach to Molecular Kinetics

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

On-the-Fly Learning and Sampling of Ligand Binding by High-Throughput Molecular Simulations

(2014) S. Doerr et al.   Journal of Chemical Theory and Computation

Variational Approach to Enhanced Sampling and Free Energy Calculations

(2014) Omar Valsson et al.   PHYSICAL REVIEW LETTERS

Perspective on the Martini model

(2013) Siewert J. Marrink et al.   CHEMICAL SOCIETY REVIEWS

Coarse-grain modelling of protein–protein interactions

(2013) Marc Baaden et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Perspective: Coarse-grained models for biomolecular systems

(2013) W. G. Noid   JOURNAL OF CHEMICAL PHYSICS

Identification of slow molecular order parameters for Markov model construction

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

Going Backward: A Flexible Geometric Approach to Reverse Transformation from Coarse Grained to Atomistic Models

(2013) Tsjerk A. Wassenaar 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

The power of coarse graining in biomolecular simulations

(2013) Helgi I. Ingólfsson et al.   Wiley Interdisciplinary Reviews-Computational Molecular Science

Coarse-Grained Models for Protein-Cell Membrane Interactions

(2013) Ryan Bradley et al.   Polymers

Neutron scattering and molecular dynamics simulations: synergetic tools to unravel structure and dynamics in polymers

(2012) Arantxa Arbe et al.   Soft Matter

Systematic coarse-graining methods for soft matter simulations – a review

(2012) Emiliano Brini et al.   Soft Matter

Coarse-grained models for protein aggregation

(2011) Chun Wu et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Why are coarse-grained force fields too fast? A look at dynamics of four coarse-grained polymers

(2011) Praveen Depa et al.   JOURNAL OF CHEMICAL PHYSICS

Markov models of molecular kinetics: Generation and validation

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

Multiscale modeling of soft matter: scaling of dynamics

(2011) Dominik Fritz et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

How Fast-Folding Proteins Fold

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

High-Throughput All-Atom Molecular Dynamics Simulations Using Distributed Computing

(2010) I. Buch et al.   Journal of Chemical Information and Modeling

Enhanced Modeling via Network Theory: Adaptive Sampling of Markov State Models

(2010) Gregory R. Bowman et al.   Journal of Chemical Theory and Computation

Reconstruction of atomistic details from coarse-grained structures

(2010) Andrzej J. Rzepiela et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY

Improved side-chain torsion potentials for the Amber ff99SB protein force field

(2010) Kresten Lindorff-Larsen et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS

ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

(2009) M. J. Harvey et al.   Journal of Chemical Theory and Computation

Adaptive resolution simulation of liquid water

(2009) Matej Praprotnik et al.   JOURNAL OF PHYSICS-CONDENSED MATTER

Multiscale simulation of soft matter systems – from the atomistic to the coarse-grained level and back

(2009) Christine Peter et al.   Soft Matter

Comparison of explicit atom, united atom, and coarse-grained simulations of poly(methyl methacrylate)

(2008) Chunxia Chen et al.   JOURNAL OF CHEMICAL PHYSICS

Well-Tempered Metadynamics: A Smoothly Converging and Tunable Free-Energy Method

(2008) Alessandro Barducci et al.   PHYSICAL REVIEW LETTERS