Ziang Li

SynFit improves protein fitness prediction by learning shared and property-specific sequence representations, outperforming existing methods in multi-objective optimization.

This paper introduces DETANGO, a deep learning framework that disentangles mutation effects on protein stability and function, identifying stable-but-inactive variants and functionally critical residues.

The paper introduces SPURS, a deep learning framework for protein stability prediction that integrates generative models and achieves accurate, scalable, and generalizable results.