| Uni-mol: A universal 3d molecular representation learning framework G Zhou, Z Gao, Q Ding, H Zheng, H Xu, Z Wei, L Zhang, G Ke | 160 | 2023 |
| Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation? G Zhou, Z Gao, Z Wei, H Zheng, G Ke arXiv preprint arXiv:2302.07061, 2023 | 10 | 2023 |
| Uni-Mol: a universal 3D molecular representation learning framework. 2023 G Zhou, Z Gao, Q Ding, H Zheng, H Xu, Z Wei, L Zhang, G Ke There is no corresponding record for this reference, 0 | 6 | |
| Predicting protein-ligand binding affinity via joint global-local interaction modeling Y Zhang, G Zhou, Z Wei, H Xu 2022 IEEE International Conference on Data Mining (ICDM), 1323-1328, 2022 | 5 | 2022 |
| Synergistic application of molecular docking and machine learning for improved binding pose Y Li, H Lin, H Yang, Y Yuan, R Zou, G Zhou, L Zhang, H Zheng National Science Open 3 (2), 20230058, 2024 | 1 | 2024 |
| Synergistic Application of Molecular Docking and Machine Learning for Improved Protein-Ligand Binding Pose Prediction H Yang, H Lin, Y Yuan, Y Li, R Zou, G Zhou, L Zhang, H Zheng | 1 | 2023 |
| Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction E Alcaide, Z Gao, G Ke, Y Li, L Zhang, H Zheng, G Zhou arXiv preprint arXiv:2405.11769, 2024 | | 2024 |
| Uni-pKa: An Accurate and Physically Consistent pKa Prediction through Protonation Ensemble Modeling H Zheng, W Luo, G Zhou, Z Zhu, Y Yuan, G Ke, Z Wei, Z Gao | | 2023 |
| Uni-pKa: An Accurate and Physically Consistent pKa Prediction through Protonation Ensemble Modeling W Luo, G Zhou, Z Zhu, G Ke, Z Wei, Z Gao, H Zheng | | 2023 |
