| GANsDTA: Predicting drug-target binding affinity using GANs L Zhao, J Wang, L Pang, Y Liu, J Zhang Frontiers in genetics 10, 1243, 2020 | 82 | 2020 |
| A novel protein subcellular localization method with CNN-XGBoost model for Alzheimer's disease L Pang, J Wang, L Zhao, C Wang, H Zhan Frontiers in genetics 9, 751, 2019 | 53 | 2019 |
| A brief review of protein–ligand interaction prediction L Zhao, Y Zhu, J Wang, N Wen, C Wang, L Cheng Computational and Structural Biotechnology Journal 20, 2831-2838, 2022 | 26 | 2022 |
| Deep reinforcement learning for data association in cell tracking J Wang, X Su, L Zhao, J Zhang Frontiers in Bioengineering and Biotechnology 8, 298, 2020 | 23 | 2020 |
| ELECTRA-DTA: a new compound-protein binding affinity prediction model based on the contextualized sequence encoding J Wang, NF Wen, C Wang, L Zhao, L Cheng Journal of cheminformatics 14 (1), 14, 2022 | 21 | 2022 |
| Conjoint feature representation of GO and protein sequence for PPI prediction based on an inception RNN attention network L Zhao, J Wang, Y Hu, L Cheng Molecular Therapy-Nucleic Acids 22, 198-208, 2020 | 17 | 2020 |
| Deep forest-based prediction of protein subcellular localization L Zhao, J Wang, MM Nabil, J Zhang Current Gene Therapy 18 (5), 268-274, 2018 | 17 | 2018 |
| DFFNDDS: prediction of synergistic drug combinations with dual feature fusion networks M Xu, X Zhao, J Wang, W Feng, N Wen, C Wang, J Wang, Y Liu, L Zhao Journal of Cheminformatics 15 (1), 33, 2023 | 13 | 2023 |
| Reliability modeling and contrastive learning for unsupervised person re-identification Z Pang, C Wang, J Wang, L Zhao Knowledge-Based Systems 263, 110263, 2023 | 12 | 2023 |
| MGPLI: exploring multigranular representations for protein–ligand interaction prediction J Wang, J Hu, H Sun, MD Xu, Y Yu, Y Liu, L Cheng Bioinformatics 38 (21), 4859-4867, 2022 | 11 | 2022 |
| Association between a novel metabolic score for insulin resistance and mortality in people with diabetes Z Wang, J Xie, J Wang, W Feng, N Liu, Y Liu Frontiers in Cardiovascular Medicine 9, 895609, 2022 | 10 | 2022 |
| Gaussian particle flow implementation of PHD filter L Zhao, J Wang, Y Li, MJ Coates Signal Processing, Sensor/Information Fusion, and Target Recognition XXV …, 2016 | 10 | 2016 |
| Micro-object motion tracking based on the probability hypothesis density particle tracker C Shi, L Zhao, J Wang, C Zhang, X Su, P Ma Journal of mathematical biology 72, 1225-1254, 2016 | 7 | 2016 |
| Validation of type 2 diabetes subgroups by simple clinical parameters: a retrospective cohort study of NHANES data from 1999 to 2014 J Xie, H Shao, T Shan, S Jing, Y Shi, J Wang, J Hu, Y Li, R Huang, N Liu, ... BMJ open 12 (3), e055647, 2022 | 5 | 2022 |
| Ontosem: an ontology semantic representation methodology for biomedical domain L Zhao, J Wang, L Cheng, C Wang 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2020 | 5 | 2020 |
| DataDTA: a multi-feature and dual-interaction aggregation framework for drug–target binding affinity prediction Y Zhu, L Zhao, N Wen, J Wang, C Wang Bioinformatics 39 (9), btad560, 2023 | 4 | 2023 |
| Using a stacked ensemble learning framework to predict modulators of protein–protein interactions M Gao, L Zhao, Z Zhang, J Wang, C Wang Computers in Biology and Medicine 161, 107032, 2023 | 4 | 2023 |
| Learning representations for gene ontology terms by jointly encoding graph structure and textual node descriptors L Zhao, H Sun, X Cao, N Wen, J Wang, C Wang Briefings in Bioinformatics 23 (5), bbac318, 2022 | 4 | 2022 |
| Marginalized Particle Flow Filter J Wang, L Zhao, X Su Circuits, Systems, and Signal Processing, 2018 | 4 | 2018 |
| Intakes of omega-3 fatty acids and risks of all-cause and cause-specific mortality in people with diabetes: a cohort study based on NHANES 1999–2014 J Xie, Z Wang, J Wang, W Feng, T Shan, S Jing, S Xiao, W Li, N Liu, Y Liu Acta Diabetologica 60 (3), 353-362, 2023 | 3 | 2023 |
Chunyu WangHarbin Institute of TechnologyVerified email at hit.edu.cn
