3.9k citations · 4.8k across the 19 of their papers we have counts for
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Making PLUMED fly: a tutorial on optimizing performance
Daniele Rapetti, Massimiliano Bonomi, Carlo Camilloni +2
PLUMED is an open-source software package that is widely used for analyzing and enhancing molecular dynamics simulations that works in conjunction with most available molecular dyn…
A Fully Quantum-Mechanical Treatment for Kaolinite
Sam Shepherd, Gareth A. Tribello, David M. Wilkins
Neural network potentials for kaolinite minerals have been fitted to data extracted from density functional theory calculation that were performed using the revPBE + D3 and revPBE…
Iterative unbiasing of quasi-equilibrium sampling
Federico Giberti, Bingqing Cheng, Gareth Aneurin Tribello +1
Atomistic modelling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation t…
Using data-reduction techniques to analyse biomolecular trajectories
Gareth A. Tribello, Piero Gasparotto
This chapter discusses the way in which dimensionality reduction algorithms such as diffusion maps and sketch-map can be used to analyze molecular dynamics trajectories. The first…
Analyzing and biasing simulations with PLUMED
Giovanni Bussi, Gareth A. Tribello
This chapter discusses how the PLUMED plugin for molecular dynamics can be used to analyze and bias molecular dynamics trajectories. The chapter begins by introducing the notion of…
Building Maps in Collective Variable Space
Ilaria Gimondi, Gareth A. Tribello, Matteo Salvalaglio
Enhanced sampling techniques such as umbrella sampling and metadynamics are now routinely used to provide information on how the thermodynamic potential, or free energy, depends on…
PLUMED 2: New feathers for an old bird
Gareth A. Tribello, Massimiliano Bonomi, Davide Branduardi +2
Enhancing sampling and analyzing simulations are central issues in molecular simulation. Recently, we introduced PLUMED, an open-source plug-in that provides some of the most popul…
A self-learning algorithm for biased molecular dynamics
Gareth A. Tribello, Michele Ceriotti, Michele Parrinello
A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Accelerati…