Protein and Machine Learning
Protein and Machine Learning
This is a living document.
Workshop: CCPBioSim workshop: structural bioinformatics resources and tools for molecular dynamics simulations.
Workshop: Machine Learning Augmented Sampling for the Molecular Science
Package: MDAnalysis
Package: GROMACS
Article: Enhanced Sampling in the Age of Machine Learning: Algorithms and Applications (2025, Chemical Reviews) *
Article: Explainable chemical artificial intelligence from accurate machine learning of real-space chemical descriptors (2025, Nature Communications)
Article: Collective Variable-Based Enhanced Sampling: From Human Learning to Machine Learning (2024, The Journal of Physical Chemistry Letters)
Article: Enhanced Sampling with Machine Learning (2024, Annual Reviews) *
Article: Interrogating RNA-Small Molecule Interactions with Structure Probing and Artificial Intelligence-Augmented Molecular Simulations (2022, Acs Central Science)
Article: Deep learning the slow modes for rare events sampling (2021, Biophysics and Computational Biology) *
Article: Machine learning for collective variable discovery and enhance sampling in biomolecular simulation (2020, Molecular Physics)
Article: Data-Drive Collective Variables for Enhanced Sampling (2020, The Journal of Physical Chemistry Letters)
Article: VAMPnets for deep learning of molecular kinetics (2018, Nature Communications)
Article: Enhanced Sampling in Molecular Dynamics Using Metadynamics, Replica-Exchange, and Temperature-Acclearation (2013, Entropy)
Masterclass: PLUMED *
Github repos: mlcolvar *
Github repos: ops_tutorial (OpenPathSampling)
Github repos: westpa ( Weighted ensemble simulation)
Github repos: DL4Proteins-notebooks
Github repos: OpenMM