CPRISP: an interpretable deep learning framework predicting circRNA-RBP interactions and guiding therapeutic discovery in neurodegeneration

Researchers developed CPRISP, a deep learning framework that predicts interactions between circular RNAs and RNA-binding proteins, improving accuracy across multiple datasets and cell lines. The model reveals conserved sequence patterns and highlights pathways linked to neurodegenerative diseases, aiding therapeutic research.