Yufeng Su

The paper introduces RDE, an unsupervised method that predicts mutation effects on protein-protein binding by estimating conformational flexibility from protein structures, outperforming existing methods.

This paper introduces a diffusion-based generative model for designing and optimizing antigen-specific antibodies by jointly modeling CDR sequences and structures.

This paper introduces ECNet, a deep learning model that uses evolutionary context to predict protein variant fitness, outperforming existing methods on multiple datasets.

The paper introduces a meta-learning framework to predict phosphorylation sites for kinases with limited experimental data, showing improved transferability and accuracy.