English
Related papers

Related papers: Infinite Switch Simulated Tempering in Force (FISS…

200 papers

We formulate and characterize a model to describe the dynamics of semiflexible polymers in the presence of activity due to motor proteins attached irreversibly to a substrate, and a transverse pulling force acting on one end of the…

Biological Physics · Physics 2016-02-12 Abhishek Chaudhuri , Debasish Chaudhuri

Proteins are the most important biomolecules for living organisms. The understanding of protein structure, function, dynamics and transport is one of most challenging tasks in biological science. In the present work, persistent homology is,…

Biomolecules · Quantitative Biology 2014-12-10 Kelin Xia , Guo-Wei Wei

We have developed a new extended replica exchange method to study thermodynamics of a system in the presence of external force. Our idea is based on the exchange between different force replicas to accelerate the equilibrium process. We…

Biomolecules · Quantitative Biology 2009-11-13 Maksim Kouza , Chin-Kun Hu , Mai Suan Li

Forced detachment of a single polymer chain, strongly-adsorbed on a solid substrate, is investigated by two complementary methods: a coarse-grained analytical dynamical model, based on the Onsager stochastic equation, and Molecular Dynamics…

Soft Condensed Matter · Physics 2014-03-27 J. Paturej , J. L. A. Dubbeldam , V. G. Rostiashvili , A. Milchev , T. A. Vilgis

We combine traction force data with Bayesian inversion to obtain an absolute estimate of the internal stress field of a cell monolayer. The method, Bayesian inversion stress microscopy (BISM), is validated using numerical simulations…

Quantitative Methods · Quantitative Biology 2016-05-04 V. Nier , S. Jain , C. T. Lim , S. Ishihara , B. Ladoux , P. Marcq

We developed a multiscale approach (MultiSCAAL) that integrates the potential of mean force (PMF) obtained from all-atomistic molecular dynamics simulations with a knowledge-based energy function for coarse-grained molecular simulations in…

Biological Physics · Physics 2010-05-10 Antonios Samiotakis , Dirar Homouz , Margaret S. Cheung

Design flow parameters are of utmost importance to chip design quality and require a painfully long time to evaluate their effects. In reality, flow parameter tuning is usually performed manually based on designers' experience in an ad hoc…

We introduce Adjoint Sampling, a highly scalable and efficient algorithm for learning diffusion processes that sample from unnormalized densities, or energy functions. It is the first on-policy approach that allows significantly more…

Developing accurate and efficient coarse-grained representations of proteins is crucial for understanding their folding, function, and interactions over extended timescales. Our methodology involves simulating proteins with molecular…

Biomolecules · Quantitative Biology 2023-10-11 Carles Navarro , Maciej Majewski , Gianni de Fabritiis

Generative models have advanced significantly in sampling material systems with continuous variables, such as atomistic structures. However, their application to discrete variables, like atom types or spin states, remains underexplored. In…

Statistical Mechanics · Physics 2025-11-18 Ping Tuo , Zezhu Zeng , Jiale Chen , Bingqing Cheng

A computational method is developed to work on an inverse equilibrium problem with an interest towards applications with protein folding. In general, we are given a set of equilibrium confgiurations and want to derive the most probable…

Biological Physics · Physics 2007-05-23 John P. Donohue

Coarse-grained (CG) molecular simulations have become a standard tool to study molecular processes on time- and length-scales inaccessible to all-atom simulations. Parameterizing CG force fields to match all-atom simulations has mainly…

Computational Physics · Physics 2023-02-07 Jonas Köhler , Yaoyi Chen , Andreas Krämer , Cecilia Clementi , Frank Noé

Simulating transition dynamics between metastable states is a fundamental challenge in dynamical systems and stochastic processes with wide real-world applications in understanding protein folding, chemical reactions and neural activities.…

Machine Learning · Computer Science 2024-10-22 Haibo Wang , Yuxuan Qiu , Yanze Wang , Rob Brekelmans , Yuanqi Du

Nested sampling is a promising method for calculating phase diagrams of materials, however, the computational cost limits its applicability if ab-initio accuracy is required. In the present work, we report on the efficient use of a…

Materials Science · Physics 2023-08-23 N. Unglert , J. Carrete , L. B. Pártay , G. K. H. Madsen

We propose an adaptive biasing algorithm aimed at enhancing the sampling of multimodal measures by Langevin dynamics. The underlying idea consists in generalizing the standard adaptive biasing force method commonly used in conjunction with…

Analysis of PDEs · Mathematics 2010-08-23 Chris Chipot , Tony Lelièvre

We report a single-copy tempering method for simulating large complex systems. In a generalized ensemble, the method uses runtime estimate of the thermal average energy computed from a novel integral identity to guide a continuous…

Biological Physics · Physics 2015-05-18 Cheng Zhang , Jianpeng Ma

Transition interface sampling (TIS) and replica exchange TIS (RETIS) are powerful methods for computing rates of rare events inaccessible to straightforward molecular dynamics (MD) simulations. Path reweighting extends their output,…

Chemical Physics · Physics 2026-05-15 Titus S. van Erp , Daniel T. Zhang , Elias Wils , Sina Safaei , An Ghysels

The kinetics of collective rearrangements in solution, such as protein folding and nanocrystal phase transitions, often involve free energy barriers that are both long and rough. Applying methods of transition path sampling to harvest…

Statistical Mechanics · Physics 2009-11-13 M. Grünwald , P. L. Geissler , C. Dellago

Bayesian optimization in large unstructured discrete spaces is often hindered by the computational cost of maximizing acquisition functions due to the absence of gradients. We propose a scalable alternative based on Thompson sampling that…

Machine Learning · Computer Science 2026-03-02 Nicolas Menet , Aleksandar Terzić , Michael Hersche , Andreas Krause , Abbas Rahimi

We present some applications of an Interacting Particle System (IPS) methodology to the field of Molecular Dynamics. This IPS method allows several simulations of a switched random process to keep closer to equilibrium at each time, thanks…

Statistical Mechanics · Physics 2009-11-11 Mathias Rousset , Gabriel Stoltz
‹ Prev 1 3 4 5 6 7 10 Next ›