Deciphering the Language of Nature: A transformer-based language model for deleterious mutations in proteins
The paper introduces MutFormer, a transformer-based model that combines self-attention and convolutional layers to predict deleterious missense mutations in human proteins, demonstrating performance comparable to or better than existing tools by effectively capturing both short-range and long-range sequence dependencies.