Quancheng Liu

StarFunc combines deep learning with template information from multiple sources to improve protein function prediction, outperforming existing methods in benchmark tests.

StoPred predicts protein complex stoichiometry using protein language models and graph attention networks, achieving higher accuracy for both homomeric and heteromeric complexes than existing methods.

EZpred improves enzyme function prediction by using unlabeled sequence homologs, achieving higher F1-scores than existing methods.

InterLabelGO+ improves protein function prediction by combining deep learning and alignment-based methods with a novel loss function and dynamic weighting, achieving strong performance in the CAFA5 challenge.