Bozitao Zhong

This paper introduces a pre-training framework that combines sequential and geometric encoders to improve protein variant prediction for enhanced bioactivity and thermostability.

This study introduces a lightweight graph neural network for protein engineering that predicts fitness and guides the design of effective mutants with improved physicochemical properties.

The paper investigates the onset of anharmonicity in a protein and its surface water around 200 K, finding they are decoupled, with the protein's transition being intrinsic and the water's being a resolution effect.