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Many biological processes occur on time scales longer than those accessible to molecular dynamics simulations. Identifying collective variables (CVs) and introducing an external potential to accelerate them is a popular approach to address…

Computational Physics · Physics 2024-10-24 Enrico Trizio , Andrea Rizzi , Pablo M. Piaggi , Michele Invernizzi , Luigi Bonati

Selection of appropriate collective variables for enhancing sampling of molecular simulations remains an unsolved problem in computational biophysics. In particular, picking initial collective variables (CVs) is particularly challenging in…

Machine Learning · Statistics 2018-05-15 Mohammad M. Sultan , Vijay S. Pande

Simulating rare events, such as the transformation of a reactant into a product in a chemical reaction typically requires enhanced sampling techniques that rely on heuristically chosen collective variables (CVs). We propose using…

Enhanced sampling algorithms have emerged as powerful methods to extend the utility of molecular dynamics simulations and allow the sampling of larger portions of the configuration space of complex systems in a given amount of simulation…

Statistical Mechanics · Physics 2022-12-19 Jérôme Hénin , Tony Lelièvre , Michael R. Shirts , Omar Valsson , Lucie Delemotte

A variety of enhanced sampling methods predict multidimensional free energy landscapes associated with biological and other molecular processes as a function of a few selected collective variables (CVs). The accuracy of these methods is…

Computational Physics · Physics 2024-04-09 Lukas Müllender , Andrea Rizzi , Michele Parrinello , Paolo Carloni , Davide Mandelli

Understanding protein conformational dynamics is essential for elucidating biological function but remains challenging due to the wide range of timescales and the complexity of collective motions. Enhanced sampling methods overcome…

Statistical Mechanics · Physics 2026-05-11 Souvik Mondal , Michael A. Sauer , Matthias Heyden

Cross-validation (CV) is one of the main tools for performance estimation and parameter tuning in machine learning. The general recipe for computing CV estimate is to run a learning algorithm separately for each CV fold, a computationally…

Machine Learning · Statistics 2015-07-02 Pooria Joulani , András György , Csaba Szepesvári

Many recently introduced enhanced sampling techniques are based on biasing coarse descriptors (collective variables) of a molecular system on the fly. Sometimes the calculation of such collective variables is expensive and becomes a…

Computational Physics · Physics 2015-09-01 Marco Jacopo Ferrarotti , Sandro Bottaro , Andrea Pérez-Villa , Giovanni Bussi

Rare event sampling is a central problem in modern computational chemistry research. Among the existing methods, transition path sampling (TPS) can generate unbiased representations of reaction processes. However, its efficiency depends on…

Computational Physics · Physics 2024-04-04 Jintu Zhang , Odin Zhang , Luigi Bonati , TingJun Hou

Metadynamics is a powerful method to accelerate molecular dynamics simulations, but its efficiency critically depends on the identification of collective variables that capture the slow modes of the process. Unfortunately, collective…

Chemical Physics · Physics 2023-07-17 Ofir Blumer , Shlomi Reuveni , Barak Hirshberg

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 popular molecular dynamics (MD) codes with implementations of a…

Computational Physics · Physics 2014-10-07 Gareth A. Tribello , Massimiliano Bonomi , Davide Branduardi , Carlo Camilloni , Giovanni Bussi

To address the time-scale limitations in molecular dynamics (MD) simulations, numerous enhanced sampling methods have been developed to expedite the exploration of complex free energy landscapes. A commonly employed approach accelerates the…

Computational Physics · Physics 2025-06-24 Zhijun Pan , Maodong Li , Dechin Chen , Yi Isaac Yang

The development of enhanced sampling methods has greatly extended the scope of atomistic simulations, allowing long-time phenomena to be studied with accessible computational resources. Many such methods rely on the identification of an…

Computational Physics · Physics 2022-06-08 Luigi Bonati , GiovanniMaria Piccini , Michele Parrinello

In molecular dynamics simulations, rare events, such as protein folding, are typically studied using enhanced sampling techniques, most of which are based on the definition of a collective variable (CV) along which acceleration occurs.…

Chemical Physics · Physics 2024-07-22 Soojung Yang , Juno Nam , Johannes C. B. Dietschreit , Rafael Gómez-Bombarelli

Diffusion-based samplers learn to sample complex, high-dimensional distributions using energies or log densities alone, without training data. Yet, they remain impractical for molecular sampling because they are often slower than molecular…

Enhanced sampling methods are indispensable in computational physics and chemistry, where atomistic simulations cannot exhaustively sample the high-dimensional configuration space of dynamical systems due to the sampling problem. A class of…

Chemical Physics · Physics 2024-04-04 Jakub Rydzewski , Ming Chen , Tushar K. Ghosh , Omar Valsson

Chemical reaction sampling critically depends on collective variables (CVs) that capture the slow degrees of freedom governing reactive transformations. However, existing reaction CVs are often defined in geometric space or learned in a…

Chemical Physics · Physics 2026-04-01 YaoKun Lei , Yi Isaac Yang

PLUMED-GUI is an interactive environment to develop and test complex PLUMED scripts within the Visual Molecular Dynamics (VMD) environment. Computational biophysicists can take advantage of both PLUMED's rich syntax to define collective…

Computational Physics · Physics 2013-12-12 Toni Giorgino

Dataset distillation aims to synthesize a compact yet representative dataset that preserves the essential characteristics of the original data for efficient model training. Existing methods mainly focus on improving data-synthetic alignment…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Jiacheng Cui , Zhaoyi Li , Xiaochen Ma , Xinyue Bi , Yaxin Luo , Zhiqiang Shen

Crystallization is one of the most important physicochemical processes which has relevance in material science, biology, and the environment. Decades of experimental and theoretical efforts have been made to understand this fundamental…

Soft Condensed Matter · Physics 2022-09-29 Neha , Vikas Tiwari , Soumya Mondal , Nisha Kumari , Tarak Karmakar
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