Fang Ge

This paper introduces AMP-D3, a framework for designing diverse and druggable antimicrobial peptides using diffusion and multimodal deep learning, achieving high accuracy in prediction and validation.

The paper evaluates variant effect predictions for ARSA gene variants, finding that a bootcamp-trained model outperformed others and that deep learning slightly improved performance over simpler methods.