| Prediction of human protein subcellular localization using deep learning L Wei, Y Ding, R Su, J Tang, Q Zou Journal of Parallel and Distributed Computing 117, 212-217, 2018 | 223 | 2018 |
| Identification of drug-side effect association via multiple information integration with centered kernel alignment Y Ding, J Tang, F Guo Neurocomputing 325, 211-224, 2019 | 196 | 2019 |
| Identification of drug-target interactions via multiple information integration Y Ding, J Tang, F Guo Information Sciences 418, 546-560, 2017 | 180 | 2017 |
| Predicting protein-protein interactions via multivariate mutual information of protein sequences Y Ding, J Tang, F Guo BMC bioinformatics 17, 1-13, 2016 | 152 | 2016 |
| Identification of drug–target interactions via dual laplacian regularized least squares with multiple kernel fusion Y Ding, J Tang, F Guo Knowledge-Based Systems 204, 106254, 2020 | 129 | 2020 |
| MK-FSVM-SVDD: a multiple kernel-based fuzzy SVM model for predicting DNA-binding proteins via support vector data description Y Zou, H Wu, X Guo, L Peng, Y Ding, J Tang, F Guo Current Bioinformatics 16 (2), 274-283, 2021 | 119 | 2021 |
| Identification of membrane protein types via multivariate information fusion with Hilbert–Schmidt independence criterion H Wang, Y Ding, J Tang, F Guo Neurocomputing 383, 257-269, 2020 | 110 | 2020 |
| Identification of drug–target interactions via fuzzy bipartite local model Y Ding, J Tang, F Guo Neural Computing and Applications 32 (14), 10303-10319, 2020 | 91 | 2020 |
| Identification of protein–protein interactions via a novel matrix-based sequence representation model with amino acid contact information Y Ding, J Tang, F Guo International journal of molecular sciences 17 (10), 1623, 2016 | 90 | 2016 |
| Identification of drug-side effect association via semisupervised model and multiple kernel learning Y Ding, J Tang, F Guo IEEE journal of biomedical and health informatics 23 (6), 2619-2632, 2018 | 85 | 2018 |
| Identification of protein–ligand binding sites by sequence information and ensemble classifier Y Ding, J Tang, F Guo Journal of Chemical Information and Modeling 57 (12), 3149-3161, 2017 | 77 | 2017 |
| MDA-SKF: similarity kernel fusion for accurately discovering miRNA-disease association L Jiang, Y Ding, J Tang, F Guo Frontiers in Genetics 9, 618, 2018 | 75 | 2018 |
| Improved detection of DNA-binding proteins via compression technology on PSSM information Y Wang, Y Ding, F Guo, L Wei, J Tang PloS one 12 (9), e0185587, 2017 | 71 | 2017 |
| SBSM-Pro: support bio-sequence machine for proteins Y Wang, Y Zhai, Y Ding, Q Zou arXiv preprint arXiv:2308.10275, 2023 | 66 | 2023 |
| Exploring associations of non-coding RNAs in human diseases via three-matrix factorization with hypergraph-regular terms on center kernel alignment H Wang, J Tang, Y Ding, F Guo Briefings in Bioinformatics 22 (5), bbaa409, 2021 | 66 | 2021 |
| Multi-scale encoding of amino acid sequences for predicting protein interactions using gradient boosting decision tree C Zhou, H Yu, Y Ding, F Guo, XJ Gong PLoS One 12 (8), e0181426, 2017 | 62 | 2017 |
| Critical evaluation of web-based prediction tools for human protein subcellular localization Y Shen, Y Ding, J Tang, Q Zou, F Guo Briefings in bioinformatics 21 (5), 1628-1640, 2020 | 60 | 2020 |
| Human protein subcellular localization identification via fuzzy model on kernelized neighborhood representation Y Ding, J Tang, F Guo Applied Soft Computing 96, 106596, 2020 | 59 | 2020 |
| FKL-Spa-LapRLS: an accurate method for identifying human microRNA-disease association L Jiang, Y Xiao, Y Ding, J Tang, F Guo Bmc Genomics 19, 11-25, 2018 | 59 | 2018 |
| Identification of drug–target interactions via multiple kernel-based triple collaborative matrix factorization Y Ding, J Tang, F Guo, Q Zou Briefings in Bioinformatics 23 (2), bbab582, 2022 | 50 | 2022 |
Jijun TangUniversity of South Carolina在 cse.sc.edu 的电子邮件经过验证
