| An effective self-supervised framework for learning expressive molecular global representations to drug discovery P Li, J Wang, Y Qiao, H Chen, Y Yu, X Yao, P Gao, G Xie, S Song Briefings in Bioinformatics 22 (6), bbab109, 2021 | 129* | 2021 |
| Deep geometric representations for modeling effects of mutations on protein-protein binding affinity X Liu, Y Luo, P Li, S Song, J Peng PLoS computational biology 17 (8), e1009284, 2021 | 80 | 2021 |
| In Situ Growth of a Cationic Polymer from the N-Terminus of Glucose Oxidase To Regulate H2O2 Generation for Cancer Starvation and H2O2 Therapy H Hao, M Sun, P Li, J Sun, X Liu, W Gao ACS Applied Materials & Interfaces 11 (10), 9756-9762, 2019 | 69 | 2019 |
| TrimNet: learning molecular representation from triplet messages for biomedicine P Li, Y Li, CY Hsieh, S Zhang, X Liu, H Liu, S Song, X Yao Briefings in Bioinformatics 22 (4), bbaa266, 2021 | 64 | 2021 |
| Site-selective in situ growth-induced self-assembly of protein–polymer conjugates into pH-responsive micelles for tumor microenvironment triggered fluorescence imaging P Li, M Sun, Z Xu, X Liu, W Zhao, W Gao Biomacromolecules 19 (11), 4472-4479, 2018 | 52 | 2018 |
| Deep generative model for drug design from protein target sequence Y Chen, Z Wang, L Wang, J Wang, P Li, D Cao, X Zeng, X Ye, T Sakurai Journal of Cheminformatics 15 (1), 38, 2023 | 34 | 2023 |
| An adaptive graph learning method for automated molecular interactions and properties predictions XY Yuquan Li, Chang-Yu Hsieh, Ruiqiang Lu, Xiaoqing Gong, Xiaorui Wang ... Nature Machine Intelligence 4 (7), 645-651, 2022 | 28 | 2022 |
| Introducing block design in graph neural networks for molecular properties prediction Y Li, P Li, X Yang, CY Hsieh, S Zhang, X Wang, R Lu, H Liu, X Yao Chemical Engineering Journal 414, 128817, 2021 | 25 | 2021 |
| Simulated annealing for optimization of graphs and sequences X Liu, P Li, F Meng, H Zhou, H Zhong, J Zhou, L Mou, S Song Neurocomputing 465, 310-324, 2021 | 18 | 2021 |
| Pairwise half-graph discrimination: A simple graph-level self-supervised strategy for pre-training graph neural networks P Li, J Wang, Z Li, Y Qiao, X Liu, F Ma, P Gao, S Song, G Xie arXiv preprint arXiv:2110.13567, 2021 | 18 | 2021 |
| Molecular language models: RNNs or transformer? Y Chen, Z Wang, X Zeng, Y Li, P Li, X Ye, T Sakurai Briefings in Functional Genomics 22 (4), 392-400, 2023 | 10 | 2023 |
| Improving drug-target affinity prediction via feature fusion and knowledge distillation R Lu, J Wang, P Li, Y Li, S Tan, Y Pan, H Liu, P Gao, G Xie, X Yao Briefings in Bioinformatics 24 (3), bbad145, 2023 | 8 | 2023 |
| Decomposing Retrosynthesis into Reactive Center Prediction and Molecule Generation X Liu, P Li, S Song bioRxiv, 677849, 2019 | 5 | 2019 |
| PASH at TREC 2020 Deep Learning Track: Dense Matching for Nested Ranking. Y Qiao, H Chen, L Cao, L Chen, P Li, J Wang, P Gao, Y Ni, G Xie TREC, 2020 | 4 | 2020 |
| Development, validation, and evaluation of a deep learning model to screen cyclin-dependent kinase 12 inhibitors in cancers T Wen, J Wang, R Lu, S Tan, P Li, X Yao, H Liu, Z Yi, L Li, S Liu, P Gao, ... European Journal of Medicinal Chemistry 250, 115199, 2023 | 3 | 2023 |
| Decomposing retrosynthesis into reactive center prediction and molecule generation. bioRxiv XG Liu, P Li, S Song | 2 | 2019 |
| Improving drug response prediction via integrating gene relationships with deep learning P Li, Z Jiang, T Liu, X Liu, H Qiao, X Yao Briefings in Bioinformatics 25 (3), bbae153, 2024 | 1 | 2024 |
| Hcl: Improving graph representation with hierarchical contrastive learning J Wang, W Li, C Hou, X Tang, Y Qiao, R Fang, P Li, P Gao, G Xie International Semantic Web Conference, 108-124, 2022 | 1 | 2022 |
| CandidateDrug4Cancer: An open molecular graph learning benchmark on drug discovery for cancer X Ye, Z Li, F Ma, Z Yi, P Li, J Wang, P Gao, Y Qiao, G Xie arXiv preprint arXiv:2203.00836, 2022 | 1 | 2022 |
| In Situ Growth of a Cationic Polymer from the N-Terminus of Glucose Oxidase To Regulate H₂O₂ Generation for Cancer Starvation and H₂O₂ Therapy H Hao, M Sun, P Li, J Sun, X Liu, W Gao | | 2019 |
