Azam Shirali

RNAtomy is a structure-aware RNA foundation model that learns structural and functional representations from geometric and conformational features, achieving strong performance on diverse tasks.

This study surveys and evaluates state-of-the-art scoring functions for protein-protein docking, comparing classical and deep learning-based approaches.

The paper introduces PIsToN, a transformer-based model for predicting protein binding interfaces, which outperforms existing methods on benchmark datasets.