| iDNA-ABF: multi-scale deep biological language learning model for the interpretable prediction of DNA methylations J Jin, Y Yu, R Wang, X Zeng, C Pang, Y Jiang, Z Li, Y Dai, R Su, Q Zou, ... Genome biology 23 (1), 219, 2022 | 47 | 2022 |
| DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis R Wang, Y Jiang, J Jin, C Yin, H Yu, F Wang, J Feng, R Su, K Nakai, ... Nucleic acids research 51 (7), 3017-3029, 2023 | 39 | 2023 |
| Predicting protein–peptide binding residues via interpretable deep learning R Wang, J Jin, Q Zou, K Nakai, L Wei Bioinformatics 38 (13), 3351-3360, 2022 | 35 | 2022 |
| Accelerating bioactive peptide discovery via mutual information-based meta-learning W He, Y Jiang, J Jin, Z Li, J Zhao, B Manavalan, R Su, X Gao, L Wei Briefings in bioinformatics 23 (1), bbab499, 2022 | 33 | 2022 |
| iDNA-ABT: advanced deep learning model for detecting DNA methylation with adaptive features and transductive information maximization Y Yu, W He, J Jin, G Xiao, L Cui, R Zeng, L Wei Bioinformatics 37 (24), 4603-4610, 2021 | 24 | 2021 |
| 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 |
| Retrosynthesis prediction with an interpretable deep-learning framework based on molecular assembly tasks Y Wang, C Pang, Y Wang, J Jin, J Zhang, X Zeng, R Su, Q Zou, L Wei Nature Communications 14 (1), 6155, 2023 | 16 | 2023 |
| Mouse4mC-BGRU: Deep learning for predicting DNA N4-methylcytosine sites in mouse genome J Jin, Y Yu, L Wei Methods 204, 258-262, 2022 | 13 | 2022 |
| CACPP: a contrastive learning-based Siamese network to identify anticancer peptides based on sequence only X Yang, J Jin, R Wang, Z Li, Y Wang, L Wei Journal of Chemical Information and Modeling, 2023 | 8 | 2023 |
| SiameseCPP: a sequence-based Siamese network to predict cell-penetrating peptides by contrastive learning X Zhang, L Wei, X Ye, K Zhang, S Teng, Z Li, J Jin, MJ Kim, T Sakurai, ... Briefings in Bioinformatics 24 (1), bbac545, 2023 | 8 | 2023 |
| DrugormerDTI: Drug Graphormer for drug–target interaction prediction J Hu, W Yu, C Pang, J Jin, NT Pham, B Manavalan, L Wei Computers in Biology and Medicine 161, 106946, 2023 | 5 | 2023 |
| ExamPle: explainable deep learning framework for the prediction of plant small secreted peptides Z Li, J Jin, Y Wang, W Long, Y Ding, H Hu, L Wei Bioinformatics 39 (3), btad108, 2023 | 5 | 2023 |
| Towards retraining-free RNA modification prediction with incremental learning J Qiao, J Jin, H Yu, L Wei Information Sciences 660, 120105, 2024 | 4 | 2024 |
| 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 |
| PLPMpro: Enhancing promoter sequence prediction with prompt-learning based pre-trained language model Z Li, J Jin, W Long, L Wei Computers in Biology and Medicine 164, 107260, 2023 | 3 | 2023 |
| CoraL: interpretable contrastive meta-learning for the prediction of cancer-associated ncRNA-encoded small peptides Z Li, J Jin, W He, W Long, H Yu, X Gao, K Nakai, Q Zou, L Wei Briefings in Bioinformatics 24 (6), bbad352, 2023 | 2 | 2023 |
| 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 |
| MolCAP: Molecular Chemical reActivity Pretraining and prompted-finetuning enhanced molecular representation learning Y Wang, J Zhang, J Jin, L Wei Computers in Biology and Medicine 167, 107666, 2023 | 1 | 2023 |
Leyi WEIProfessor, School of Software, Shandong UniversityVerified email at sdu.edu.cn
