I am a bioinformatics researcher dedicated to addressing two fundamental challenges in the field: protein structure prediction and functional annotation, with the goal of advancing their applications in complex biological systems.

Protein structure prediction

• Co-developed the mTM-align algorithm for multi-template structural alignment and established its widely used online server (adopted by researchers in over 50 countries).

• Contributed to cutting-edge deep learning-based methods, including MapPred and trRosetta (trRosetta ranked among top performers in recent CASP competitions).

• Extended the trRosetta framework to RNA structure prediction, creating trRosettaRNA, which outperformed other deep learning methods in CASP15 and RNA-Puzzles experiments.

Protein function prediction

• Developed pioneering tools (DisoRDPbind, CLIP) for identifying functional motifs in intrinsically disordered proteins (IDPs), demonstrating superior accuracy in predicting biomolecule-binding regions.

• Designed sequence-based binding site predictors (NucBind, CoABind) and enhanced databases (COACH-D, Q-BioLip) to support protein-ligand interaction studies.

Future Directions

• Deciphering the dynamic structure and functional mechanisms of IDPs.

• Advancing computational strategies for protein directed evolution.

Academic Contributions

• Published 40+ SCI-indexed papers in leading journals including PNAS, Nature Communications, Nature Protocols, Advanced Science, and Nucleic Acids Research (total citations >3,000; one paper cited 800+ times).

• Principal Investigator of 4 national grants, including the NSFC Excellent Young Scholars Program and sub-projects of China's National Key R&D Program.