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 | 50 | 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 | 13 | 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 | 5 | 2022 |
Abseval: An agent-based framework for script evaluation S Liang, B Zhang, J Zhao, K Liu Proceedings of the 2024 Conference on Empirical Methods in Natural Language …, 2024 | 2 | 2024 |
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 | 2 | 2024 |
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 |
ZhuJiu-Knowledge: A Fairer Platform for Evaluating Multiple Knowledge Types in Large Language Models P Du, S Liang, B Zhang, P Cao, Y Chen, K Liu, J Zhao Proceedings of the 2024 Conference of the North American Chapter of the …, 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 |