| DeepPROTACs is a deep learning-based targeted degradation predictor for PROTACs F Li, Q Hu, X Zhang, R Sun, Z Liu, S Wu, S Tian, X Ma, Z Dai, X Yang, ... Nature communications 13 (1), 7133, 2022 | 67 | 2022 |
| Recent advances in predicting protein–protein interactions with the aid of artificial intelligence algorithms S Li, S Wu, L Wang, F Li, H Jiang, F Bai Current Opinion in Structural Biology 73, 102344, 2022 | 37 | 2022 |
| DeepSA: a deep-learning driven predictor of compound synthesis accessibility S Wang, L Wang, F Li, F Bai Journal of Cheminformatics 15 (1), 103, 2023 | 11 | 2023 |
| PPI-Miner: A Structure and Sequence Motif Co-Driven Protein–Protein Interaction Mining and Modeling Computational Method L Wang, F Li, X Ma, Y Cang, F Bai Journal of Chemical Information and Modeling 62 (23), 6160-6171, 2022 | 7 | 2022 |
| DiffPROTACs is a deep learning-based generator for proteolysis targeting chimeras F Li, Q Hu, Y Zhou, H Yang, F Bai Briefings in bioinformatics 25 (5), bbae358, 2024 | 1 | 2024 |
| MAI-TargetFisher: A proteome-wide drug target prediction method synergetically enhanced by artificial intelligence and physical modeling S Li, P Ren, L Wang, Q Han, F Li, H Li, F Bai Acta Pharmacologica Sinica, 1-14, 2025 | | 2025 |
| NesT-NABind: a Nested Transformer for Nucleic Acid-Binding Site Prediction on Protein Surface X Ma, F Li, Q Chen, S Gao, F Bai Journal of Chemical Information and Modeling, 2025 | | 2025 |
| PROTAC-Databank: The Present Largest Integrated Resource of PROTACs, Enabling the Enhanced DeepPROTACs 2.0 for Degradation Prediction F Bai, S Tian, Y Tang, F Li, Z Li | | 2024 |
