activity
20132026
most citedArcaNN: automated enhanced sampling generation of training sets for chemically reactive machine learning interatomic potentials

34 citations · 52 across the 8 of their papers we have counts for

collaborators

8 papers

cond-mat.soft2026

Molecular signatures of pressure-induced phase transitions in a lipid bilayer

Yanna Gautier, Guillaume Stirnemann, Jérôme Hénin

Understanding how lipid bilayers respond to pressure is essential for interpreting the coupling between membrane proteins and their native environments. Here, we use all-atom molec…

cond-mat.stat-mech2025

Hamiltonian replica exchange augmented with diffusion-based generative models and importance sampling to assess biomolecular conformational basins and barriers

Zakarya Benayad, Guillaume Stirnemann

Enhanced sampling techniques are essential for exploring biomolecular conformational dynamics that occur on timescales inaccessible to conventional molecular dynamics (MD) simulati…

cs.CV2025

Clustering data by reordering them

Axel Descamps, Sélène Forget, Aliénor Lahlou +5

Grouping elements into families to analyse them separately is a standard analysis procedure in many areas of sciences. We propose herein a new algorithm based on the simple idea th…

physics.ed-ph2024★ 2 cited

PLUMED Tutorials: a collaborative, community-driven learning ecosystem

Gareth A. Tribello, Massimiliano Bonomi, Giovanni Bussi +60

In computational physics, chemistry, and biology, the implementation of new techniques in a shared and open source software lowers barriers to entry and promotes rapid scientific p…

physics.chem-ph2024★ 34 cited

ArcaNN: automated enhanced sampling generation of training sets for chemically reactive machine learning interatomic potentials

Rolf David, Miguel de la Puente, Axel Gomez +3

The emergence of artificial intelligence has profoundly impacted computational chemistry, particularly through machine-learned potentials (MLPs), which offer a balance of accuracy…

cond-mat.soft2023

On the validity of some equilibrium models for thermodiffusion

Mario Araujo-Rocha, Alejandro Diaz-Marquez, Guillaume Stirnemann

When applied to binary solutions, thermal gradients lead to the generation of concentration-gradients and thus to inhomogeneous systems. While being known for more than 150 years,…

physics.chem-ph2022★ 10 cited

Explicit models of motions to understand protein side-chain dynamics

Nicolas Bolik-Coulon, Olivier Languin-Cattoën, Diego Carnevale +5

Nuclear magnetic relaxation is widely used to probe protein dynamics. For decades, most analyses of relaxation in proteins have relied successfully on the model-free approach, forg…

physics.bio-ph2013★ 6 cited

When does TMAO fold a polymer chain and urea unfold it?

Jagannath Mondal, Guillaume Stirnemann, B. J. Berne

Longstanding mechanistic questions about the role of protecting osmolyte trimethylamine N- oxide (TMAO) which favors protein folding and the denaturing osmolyte urea are addressed…