most citedMachine Learning for RNA Secondary Structure Prediction: a review of current methods and challenges

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

q-bio.BM2026

Enhanced sampling and cryo-EM data resolve magnesium binding to RNA

Olivier Languin-Cattoën, Elisa Posani, Giovanni Bussi

Magnesium ions are essential for RNA structure but difficult to model due to slow binding kinetics and experimental limitations. We present an enhanced-sampling strategy that accel…

physics.chem-ph2026

Bayesian Sampling of Structural Ensembles: The Role of Ensemble-Counting Measures

Ivan Gilardoni, Giovanni Bussi

Structural ensemble refinement is widely used to integrate molecular simulations with experimental measurements. While most applications focus on the maximum-a-posteriori (MAP) ens…

q-bio.BM2026

MERGE-RNA: a physics-based model to predict RNA secondary structure ensembles with chemical probing

Giuseppe Sacco, Jianhui Li, Redmond P. Smyth +2

RNA function is tied to secondary structure, operating through dynamic and heterogeneous structural ensembles. While current analysis tools typically output single static structure…

q-bio.BM20262 cited

Machine Learning for RNA Secondary Structure Prediction: a review of current methods and challenges

Giuseppe Sacco, Giovanni Bussi, Guido Sanguinetti

Predicting the secondary structure of RNA is a core challenge in computational biology, essential for understanding molecular function and designing novel therapeutics. The field h…

physics.comp-ph2025

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…