Xiaoya Wang

This study uses generative modeling and biochemistry to improve luciferase activity and stability by engineering its active center and scaffold, achieving a 50% success rate for single mutants.

This paper compares deep learning and ensemble learning models for predicting food protein allergenicity, finding that the transformer model achieved the highest AUC of 0.9578.

This study develops an XGBoost model to predict antihypertensive peptides from food, achieving high accuracy and efficiency compared to other models.