Yue Cao

TALE is a deep learning model for protein function annotation that uses joint sequence-label embeddings to improve generalizability to novel sequences, species, and functions.

This paper develops a deep generative model, gcWGAN, to design novel protein folds using sequence-structure data, achieving higher fold coverage and sequence diversity than a competing method.

This paper introduces a weakly supervised regression model to predict pathogenicity of missense variants and infer molecular mechanisms from imprecise annotations.