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 …

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most
pluripotent chemical species in molecular biology, and its functions are intimately linked to …

Markov (state) models (MSMs) and related models of molecular kinetics have recently
received a surge of interest as they can systematically reconcile simulation data from either …

Inspired by the success of deep learning techniques in the physical and chemical sciences,
we apply a modification of an autoencoder type deep neural network to the task of …

It has recently become practical to construct Markov state models (MSMs) that reproduce the
long-time statistical conformational dynamics of biomolecules using data from molecular …

A goal in the kinetic characterization of a macromolecular system is the description of its
slow relaxation processes via (i) identification of the structural changes involved in these …

Understanding the structural mechanisms of protein–ligand binding and their dependence
on protein sequence and conformation is of fundamental importance for biomedical …

All soluble proteins populate conformational ensembles that together constitute the native
state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the …

De novo protein design is a longstanding fundamental goal of synthetic biology, but has
been hindered by the difficulty in reliable prediction of accurate high-resolution protein …

The eigenvalues and eigenvectors of the molecular dynamics propagator (or transfer
operator) contain the essential information about the molecular thermodynamics and …