Heqi Sun

RNASTOP predicts and optimizes mRNA chemical stability using deep learning, improving accuracy by 13% and reducing free energy in a vaccine sequence.

EnzOracle predicts enzyme environmental adaptation traits from sequence using a mixture-of-experts framework, showing strong accuracy and mechanism-aware validation.

ProStab predicts protein stability changes upon mutations using a deep learning framework combining sequence and structure information, showing strong performance and experimental validation.

This paper introduces Hot2Mol, a deep learning framework for designing drug-like PPI inhibitors by generating molecules that mimic hot-spot residues, showing improved performance over baselines.

This paper introduces MultiPPIMI, a deep learning framework that predicts PPI-modulator interactions without requiring target structure or reference modulators, achieving high AUROC scores in benchmark tests.