| Explainable deep hypergraph learning modeling the peptide secondary structure prediction Y Jiang, R Wang, J Feng, J Jin, S Liang, Z Li, Y Yu, A Ma, R Su, Q Zou, ... Advanced Science 10 (11), 2206151, 2023 | 22 | 2023 |
| Rm-LR: A long-range-based deep learning model for predicting multiple types of RNA modifications S Liang, Y Zhao, J Jin, J Qiao, D Wang, Y Wang, L Wei Computers in Biology and Medicine 164, 107238, 2023 | 4 | 2023 |
| MechRetro is a chemical-mechanism-driven graph learning framework for interpretable retrosynthesis prediction and pathway planning Y Wang, C Pang, Y Wang, Y Jiang, J Jin, S Liang, Q Zou, L Wei arXiv preprint arXiv:2210.02630, 2022 | 4 | 2022 |
| Explainable deep graph learning accurately modeling the peptide secondary structure prediction Y Jiang, R Wang, J Feng, J Jin, S Liang, Z Li, Y Yu, A Ma, R Su, Q Zou, ... | 2 | 2022 |
| StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides D Wang, J Jin, Z Li, Y Wang, M Fan, S Liang, R Su, L Wei Bioinformatics 40 (2), btae057, 2024 | 1 | 2024 |
| PHAT: interpretable prediction of peptide secondary structures using hypergraph multi-head attention network and transfer learning Y Jiang, R Wang, J Feng, J Jin, S Liang, Z Li, Y Yu, A Ma, R Su, Q Zou, ... bioRxiv, 2022.06. 09.495580, 2022 | | 2022 |
