| Positive-unlabeled learning in bioinformatics and computational biology: a brief review F Li, S Dong, A Leier, M Han, X Guo, J Xu, X Wang, S Pan, C Jia, Y Zhang, ... Briefings in bioinformatics 23 (1), bbab461, 2022 | 47 | 2022 |
| Leveraging the attention mechanism to improve the identification of DNA N6-methyladenine sites Y Zhang, Y Liu, J Xu, X Wang, X Peng, J Song, DJ Yu Briefings in bioinformatics 22 (6), bbab351, 2021 | 25 | 2021 |
| ASPIRER: a new computational approach for identifying non-classical secreted proteins based on deep learning X Wang, F Li, J Xu, J Rong, GI Webb, Z Ge, J Li, J Song Briefings in Bioinformatics 23 (2), bbac031, 2022 | 23 | 2022 |
| RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins X Peng, X Wang, Y Guo, Z Ge, F Li, X Gao, J Song Briefings in bioinformatics 23 (4), bbac215, 2022 | 18 | 2022 |
| Graphormerdti: a graph transformer-based approach for drug-target interaction prediction M Gao, D Zhang, Y Chen, Y Zhang, Z Wang, X Wang, S Li, Y Guo, ... Computers in Biology and Medicine 173, 108339, 2024 | 9 | 2024 |
| PreAcrs: a machine learning framework for identifying anti-CRISPR proteins L Zhu, X Wang, F Li, J Song BMC bioinformatics 23 (1), 444, 2022 | 8 | 2022 |
| Targeting tumor heterogeneity: multiplex-detection-based multiple instance learning for whole slide image classification Z Wang, Y Bi, T Pan, X Wang, C Bain, R Bassed, S Imoto, J Yao, RJ Daly, ... Bioinformatics 39 (3), btad114, 2023 | 7 | 2023 |
| TIMER is a Siamese neural network-based framework for identifying both general and species-specific bacterial promoters Y Zhu, F Li, X Guo, X Wang, LJM Coin, GI Webb, J Song, C Jia Briefings in Bioinformatics 24 (4), bbad209, 2023 | 5 | 2023 |
| PmxPred: A data-driven approach for the identification of active polymyxin analogues against gram-negative bacteria X Wang, N Patil, F Li, Z Wang, H Zhan, D Schmidt, P Thompson, Y Guo, ... Computers in Biology and Medicine 168, 107681, 2024 | 3 | 2024 |
| SMG: self-supervised masked graph learning for cancer gene identification Y Cui, Z Wang, X Wang, Y Zhang, Y Zhang, T Pan, Z Zhang, S Li, Y Guo, ... Briefings in Bioinformatics 24 (6), bbad406, 2023 | 2 | 2023 |
| Deep learning approaches for non-coding genetic variant effect prediction: current progress and future prospects X Wang, F Li, Y Zhang, S Imoto, HH Shen, S Li, Y Guo, J Yang, J Song Briefings in Bioinformatics 25 (5), bbae446, 2024 | | 2024 |
| CoPRA: Bridging Cross-domain Pretrained Sequence Models with Complex Structures for Protein-RNA Binding Affinity Prediction R Han, X Liu, T Pan, J Xu, X Wang, W Lan, Z Li, Z Wang, J Song, G Wang, ... arXiv preprint arXiv:2409.03773, 2024 | | 2024 |
| HPClas: A data‐driven approach for identifying halophilic proteins based on catBoost S Hu, X Wang, Z Wang, M Jiang, S Wang, W Wang, J Song, G Zhang mLife, 2024 | | 2024 |
| SCREEN: a graph-based contrastive learning tool to infer catalytic residues and assess mutation tolerance in enzymes T Pan, Y Bi, X Wang, Y Zhang, GI Webb, R Gasser, L Kurgan, J Song bioRxiv, 2024.06. 27.601004, 2024 | | 2024 |
| Designing Effective Predictors of Protein Post-Translational Modifications Using iLearnPlus Z Chen, F Li, X Wang, Y Wang, L Kurgan, J Song Machine Learning in Bioinformatics of Protein Sequences: Algorithms …, 2023 | | 2023 |
