Cross-Attention Over RNA And Protein Sequences Enables Generalizable Interaction Prediction (opens in new tab)

Computational predictions are essential to characterize the RNA-protein interaction landscape, yet a persistent gap between benchmark performance and practical utility suggests that current models have limited generalization capabilities. To address this issue, we present CORAL (Cross-attention for RNA-protein Association Learning), a deep learning framework for the prediction of RNA--protein interactions that integrates pretrained protein (ESM-2) and RNA (DNABERT2) language models through bi...