232 citations · 335 across the 3 of their papers we have counts for
3 papers
Perspective: Markov Models for Long-Timescale Biomolecular Dynamics
Christian R. Schwantes, Robert T. McGibbon, Vijay S. Pande
Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experimen…
Variational cross-validation of slow dynamical modes in molecular kinetics
Robert T. McGibbon, Vijay S. Pande
Markov state models (MSMs) are a widely used method for approximating the eigenspectrum of the molecular dynamics propagator, yielding insight into the long-timescale statistical k…
Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models
Robert T. McGibbon, Bharath Ramsundar, Mohammad M. Sultan +2
We present a machine learning framework for modeling protein dynamics. Our approach uses L1-regularized, reversible hidden Markov models to understand large protein datasets genera…