Lirong Zheng

This paper introduces CyTRACE, a genetically encoded framework for recording cytosolic activity and archiving molecules over time in mammalian cells.

This paper designs an engineered PET hydrolase, VenusPETase, using deep learning to enhance PET depolymerization efficiency and thermostability, achieving high TPA yields and complete degradation of commercial PET.

The paper introduces GLOBE, a brain-wide single-cell recording technology, and demonstrates its use in capturing Fos transcriptional activity across a mouse brain over time.

This paper introduces CytoTape, a tool for continuous, multiplexed recording of gene regulation dynamics over weeks at single-cell resolution, and demonstrates its use in measuring transcription factor activities.

This paper uses a protein language model and structural representation tree to discover improved PET hydrolases, identifying KbPETase with higher thermal stability and degradation activity.

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.