We also discuss key challenges, such as the generalization crisis, data scarcity, and the rise of RNA #foundationmodels, and outline future directions toward predicting dynamic structural ensembles.

We survey the rapidly evolving field of machine learning for RNA 2D prediction, from classical thermodynamic models to #deeplearning and hybrid physics-based approaches.

PLUMED is widely used to analyze and enhance #moleculardynamics simulations.
This tutorial shows how to benchmark and optimize its #performance, explaining tricks to speed up calculations involving large sets of distances, angles, or torsions. ⚙️

Elisa also contributed to the joint analysis of submissions and cryo-EM maps with @rachael-kretsch.bsky.social — a great example of collaboration across labs. 🤝 Congratulations to all participants!

This collaborative work reports the results of a community-wide #CASP16 challenge to model #RNA hydration using #cryoEM data. Our group participated with a submission by @ollyfutur.bsky.social, Elisa Posani, and @bussigio.bsky.social, which performed very well. 🎯

And thanks to the opponents @jmbujnicki.bsky.social and @giuliapalermo.bsky.social for evaluating Elisa's work, and sharing their recent research at SISSA

And thanks to the opponents Jürgen Köfinger and Julija Zavadlav for evaluating Ivan's work, and sharing their recent research at SISSA