| Multi-modal molecule structure–text model for text-based retrieval and editing S Liu, W Nie, C Wang, J Lu, Z Qiao, L Liu, J Tang, C Xiao, A Anandkumar Nature Machine Intelligence 5 (12), 1447-1457, 2023 | 118 | 2023 |
| Torchdrug: A powerful and flexible machine learning platform for drug discovery Z Zhu, C Shi, Z Zhang, S Liu, M Xu, X Yuan, Y Zhang, J Chen, H Cai, J Lu, ... arXiv preprint arXiv:2202.08320, 2022 | 77 | 2022 |
| Peer: a comprehensive and multi-task benchmark for protein sequence understanding M Xu, Z Zhang, J Lu, Z Zhu, Y Zhang, M Chang, R Liu, J Tang Advances in Neural Information Processing Systems 35, 35156-35173, 2022 | 73 | 2022 |
| A text-guided protein design framework S Liu, Y Li, Z Li, A Gitter, Y Zhu, J Lu, Z Xu, W Nie, A Ramanathan, C Xiao, ... arXiv preprint arXiv:2302.04611, 2023 | 46 | 2023 |
| Protein sequence and structure co-design with equivariant translation C Shi, C Wang, J Lu, B Zhong, J Tang The Eleventh International Conference on Learning Representations, 2022 | 40 | 2022 |
| ReLMole: Molecular representation learning based on two-level graph similarities Z Ji, R Shi, J Lu, F Li, Y Yang Journal of Chemical Information and Modeling 62 (22), 5361-5372, 2022 | 24 | 2022 |
| Embeddti: enhancing the molecular representations via sequence embedding and graph convolutional network for the prediction of drug-target interaction Y Jin, J Lu, R Shi, Y Yang Biomolecules 11 (12), 1783, 2021 | 21 | 2021 |
| Towards foundational models for molecular learning on large-scale multi-task datasets D Beaini, S Huang, JA Cunha, Z Li, G Moisescu-Pareja, O Dymov, ... The Twelfth International Conference on Learning Representations (ICLR 2024), 2023 | 16 | 2023 |
| KenDTI: An ensemble model for predicting drug-target interaction by integrating multi-source information Z Yu, J Lu, Y Jin, Y Yang IEEE/ACM Transactions on Computational Biology and Bioinformatics 18 (4 …, 2021 | 14* | 2021 |
| Str2str: A score-based framework for zero-shot protein conformation sampling J Lu, B Zhong, Z Zhang, J Tang The Twelfth International Conference on Learning Representations (ICLR 2024), 2024 | 11 | 2024 |
| Score-based enhanced sampling for protein molecular dynamics J Lu, B Zhong, J Tang ICML 2023 Workshop on Structured Probabilistic Inference {\&} Generative …, 2023 | 5 | 2023 |
| GraphCG: Unsupervised discovery of steerable factors in graphs S Liu, C Wang, W Nie, H Wang, J Lu, B Zhou, J Tang | 5 | 2022 |
| Structure-informed protein language model Z Zhang, J Lu, V Chenthamarakshan, A Lozano, P Das, J Tang arXiv preprint arXiv:2402.05856, 2024 | 3 | 2024 |
| Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled S Liu, C Wang, J Lu, W Nie, H Wang, Z Li, B Zhou, J Tang Transactions on Machine Learning Research, 2024 | 2 | 2024 |
| ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation Z Zhang, J Lu, V Chenthamarakshan, A Lozano, P Das, J Tang arXiv preprint arXiv:2402.07955, 2024 | 1 | 2024 |
| Structure Language Models for Protein Conformation Generation J Lu, X Chen, SZ Lu, C Shi, H Guo, Y Bengio, J Tang arXiv preprint arXiv:2410.18403, 2024 | | 2024 |
| Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations J Lu, Z Zhang, B Zhong, C Shi, J Tang arXiv preprint arXiv:2402.10433, 2024 | | 2024 |
| PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding (Supplementary Material) M Xu, Z Zhang, J Lu, Z Zhu, Y Zhang, C Ma, R Liu, J Tang | | |
| Illuminating Protein Function Prediction through Inter-Protein Similarity Modeling Z Zhang, J Lu, V Chenthamarakshan, A Lozano, P Das, J Tang | | |
