| Prediction of lncRNA–disease associations based on inductive matrix completion C Lu, M Yang, F Luo, FX Wu, M Li, Y Pan, Y Li, J Wang Bioinformatics 34 (19), 3357-3364, 2018 | 220 | 2018 |
| Computational drug repositioning using low-rank matrix approximation and randomized algorithms H Luo, M Li, S Wang, Q Liu, Y Li, J Wang Bioinformatics 34 (11), 1904-1912, 2018 | 193 | 2018 |
| Protein–protein interaction site prediction through combining local and global features with deep neural networks M Zeng, F Zhang, FX Wu, Y Li, J Wang, M Li Bioinformatics 36 (4), 1114-1120, 2020 | 181 | 2020 |
| Gaining competitive intelligence from social media data: Evidence from two largest retail chains in the world W He, J Shen, X Tian, Y Li, V Akula, G Yan, R Tao Industrial management & data systems 115 (9), 1622-1636, 2015 | 162 | 2015 |
| Automated ICD-9 coding via a deep learning approach M Li, Z Fei, M Zeng, FX Wu, Y Li, Y Pan, J Wang IEEE/ACM transactions on computational biology and bioinformatics 16 (4 …, 2018 | 127 | 2018 |
| Biomedical data and computational models for drug repositioning: a comprehensive review H Luo, M Li, M Yang, FX Wu, Y Li, J Wang Briefings in bioinformatics 22 (2), 1604-1619, 2021 | 126 | 2021 |
| Clinical big data and deep learning: Applications, challenges, and future outlooks Y Yu, M Li, L Liu, Y Li, J Wang Big Data Mining and Analytics 2 (4), 288-305, 2019 | 118 | 2019 |
| Drug repositioning based on bounded nuclear norm regularization M Yang, H Luo, Y Li, J Wang Bioinformatics 35 (14), i455-i463, 2019 | 117 | 2019 |
| A survey of matrix completion methods for recommendation systems A Ramlatchan, M Yang, Q Liu, M Li, J Wang, Y Li Big Data Mining and Analytics 1 (4), 308-323, 2018 | 111 | 2018 |
| Identifying at-risk students for early interventions—A time-series clustering approach JL Hung, MC Wang, S Wang, M Abdelrasoul, Y Li, W He IEEE Transactions on Emerging Topics in Computing 5 (1), 45-55, 2015 | 107 | 2015 |
| Predicting drug–target interaction using positive-unlabeled learning W Lan, J Wang, M Li, J Liu, Y Li, FX Wu, Y Pan Neurocomputing 206, 50-57, 2016 | 95 | 2016 |
| Context-based features enhance protein secondary structure prediction accuracy A Yaseen, Y Li Journal of chemical information and modeling 54 (3), 992-1002, 2014 | 83 | 2014 |
| A deep learning framework for identifying essential proteins by integrating multiple types of biological information M Zeng, M Li, Z Fei, FX Wu, Y Li, Y Pan, J Wang IEEE/ACM transactions on computational biology and bioinformatics 18 (1 …, 2019 | 80 | 2019 |
| DeepFunc: a deep learning framework for accurate prediction of protein functions from protein sequences and interactions F Zhang, H Song, M Zeng, Y Li, L Kurgan, M Li Proteomics 19 (12), 1900019, 2019 | 77 | 2019 |
| DeepDSC: A deep learning method to predict drug sensitivity of cancer cell lines M Li, Y Wang, R Zheng, X Shi, Y Li, F Wu, J Wang IEEE/ACM transactions on computational biology and bioinformatics, 2019 | 77 | 2019 |
| DeepDTAF: a deep learning method to predict protein–ligand binding affinity K Wang, R Zhou, Y Li, M Li Briefings in Bioinformatics 22 (5), bbab072, 2021 | 68 | 2021 |
| Improving Performance via Computational Replication on a Large-Scale Computational Grid. Y Li, M Mascagni CCGRID 3, 442, 2003 | 68 | 2003 |
| AttentionDTA: prediction of drug–target binding affinity using attention model Q Zhao, F Xiao, M Yang, Y Li, J Wang 2019 IEEE international conference on bioinformatics and biomedicine (BIBM …, 2019 | 67 | 2019 |
| Efficient randomized algorithms for the fixed-precision low-rank matrix approximation W Yu, Y Gu, Y Li SIAM Journal on Matrix Analysis and Applications 39 (3), 1339-1359, 2018 | 66 | 2018 |
| SDLDA: lncRNA-disease association prediction based on singular value decomposition and deep learning M Zeng, C Lu, F Zhang, Y Li, FX Wu, Y Li, M Li Methods 179, 73-80, 2020 | 64 | 2020 |
Jianxin WangSchool of Computer Science and Engineering, Central South university在 mail.csu.edu.cn 的电子邮件经过验证
