Past, present, and future perspectives on computer-aided drug design methodologies
The application of computational approaches in drug discovery has been consolidated in
the last decades. These families of techniques are usually grouped under the common …
the last decades. These families of techniques are usually grouped under the common …
Solving high-dimensional Hamilton–Jacobi–Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space
Optimal control of diffusion processes is intimately connected to the problem of solving
certain Hamilton–Jacobi–Bellman equations. Building on recent machine learning inspired …
certain Hamilton–Jacobi–Bellman equations. Building on recent machine learning inspired …
A review of Girsanov reweighting and of square root approximation for building molecular Markov state models
Dynamical reweighting methods permit to estimate kinetic observables of a stochastic
process governed by a target potential V ̃ (x) from trajectories that have been generated at a …
process governed by a target potential V ̃ (x) from trajectories that have been generated at a …
Molecular free energies, rates, and mechanisms from data-efficient path sampling simulations
Molecular dynamics is a powerful tool for studying the thermodynamics and kinetics of
complex molecular events. However, these simulations can rarely sample the required time …
complex molecular events. However, these simulations can rarely sample the required time …
Transport meets variational inference: Controlled monte carlo diffusions
Connecting optimal transport and variational inference, we present a principled and
systematic framework for sampling and generative modelling centred around divergences …
systematic framework for sampling and generative modelling centred around divergences …
Rare event algorithm study of extreme warm summers and heatwaves over Europe
The analysis of extremes in climate models is hindered by the lack of statistics due to the
computational costs required to run simulations long enough to sample rare events. We …
computational costs required to run simulations long enough to sample rare events. We …
Explore protein conformational space with variational autoencoder
Molecular dynamics (MD) simulations have been actively used in the study of protein
structure and function. However, extensive sampling in the protein conformational space …
structure and function. However, extensive sampling in the protein conformational space …
Variational and optimal control representations of conditioned and driven processes
R Chetrite, H Touchette - Journal of Statistical Mechanics: Theory …, 2015 - iopscience.iop.org
We have shown recently that a Markov process conditioned on rare events involving time-
integrated random variables can be described in the long-time limit by an effective Markov …
integrated random variables can be described in the long-time limit by an effective Markov …
Predicting residence time and drug unbinding pathway through scaled molecular dynamics
Computational approaches currently assist medicinal chemistry through the entire drug
discovery pipeline. However, while several computational tools and strategies are available …
discovery pipeline. However, while several computational tools and strategies are available …
Adaptive sampling of large deviations
G Ferré, H Touchette - Journal of Statistical Physics, 2018 - Springer
We introduce and test an algorithm that adaptively estimates large deviation functions
characterizing the fluctuations of additive functionals of Markov processes in the long-time …
characterizing the fluctuations of additive functionals of Markov processes in the long-time …