Large-scale computational molecular models provide scientists a means to investigate the
effect of microscopic details on emergent mesoscopic behavior. Elucidating the relationship …

Unsupervised learning is becoming an essential tool to analyze the increasingly large
amounts of data produced by atomistic and molecular simulations, in material science, solid …

INTRODUCTION Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-
2) have been circulating worldwide since the beginning of the pandemic. Some are termed …

Machine learning (ML) is transforming all areas of science. The complex and time-
consuming calculations in molecular simulations are particularly suitable for an ML …

The development of enhanced sampling methods has greatly extended the scope of
atomistic simulations, allowing long-time phenomena to be studied with accessible …

INTRODUCTION Statistical mechanics aims to compute the average behavior of physical
systems on the basis of their microscopic constituents. For example, what is the probability …

The weighted ensemble (WE) strategy has been demonstrated to be highly efficient in
generating pathways and rate constants for rare events such as protein folding and protein …

Coarse-grained (CG) molecular dynamics enables the study of biological processes at
temporal and spatial scales that would be intractable at an atomistic resolution. However …

Although molecular dynamics simulations have become a useful tool in essentially all fields
of chemistry, condensed matter physics, materials science, and biology, there is still a large …

Markov state models (MSMs) are a powerful framework for analyzing dynamical systems,
such as molecular dynamics (MD) simulations, that have gained widespread use over the …