| NCMCMDA: miRNA–disease association prediction through neighborhood constraint matrix completion X Chen, LG Sun, Y Zhao Briefings in bioinformatics 22 (1), 485-496, 2021 | 160 | 2021 |
| Adaptive boosting-based computational model for predicting potential miRNA-disease associations Y Zhao, X Chen, J Yin Bioinformatics 35 (22), 4730-4738, 2019 | 143 | 2019 |
| Deep-belief network for predicting potential miRNA-disease associations X Chen, TH Li, Y Zhao, CC Wang, CC Zhu Briefings in bioinformatics 22 (3), bbaa186, 2021 | 120 | 2021 |
| ELLPMDA: ensemble learning and link prediction for miRNA-disease association prediction X Chen, Z Zhou, Y Zhao RNA biology 15 (6), 807-818, 2018 | 67 | 2018 |
| Anticancer drug response prediction in cell lines using weighted graph regularized matrix factorization NN Guan, Y Zhao, CC Wang, JQ Li, X Chen, X Piao Molecular therapy-nucleic acids 17, 164-174, 2019 | 65 | 2019 |
| Anti-cancer drug response prediction using neighbor-based collaborative filtering with global effect removal H Liu, Y Zhao, L Zhang, X Chen Molecular Therapy-Nucleic Acids 13, 303-311, 2018 | 60 | 2018 |
| In Silico prediction of small molecule-miRNA associations based on the HeteSim algorithm J Qu, X Chen, YZ Sun, Y Zhao, SB Cai, Z Ming, ZH You, JQ Li Molecular Therapy-Nucleic Acids 14, 274-286, 2019 | 55 | 2019 |
| Human microbe-disease association prediction based on adaptive boosting LH Peng, J Yin, L Zhou, MX Liu, Y Zhao Frontiers in microbiology 9, 2440, 2018 | 53 | 2018 |
| Predicting potential small molecule–miRNA associations based on bounded nuclear norm regularization X Chen, C Zhou, CC Wang, Y Zhao Briefings in Bioinformatics 22 (6), bbab328, 2021 | 48 | 2021 |
| SNMFSMMA: using symmetric nonnegative matrix factorization and Kronecker regularized least squares to predict potential small molecule-microRNA association Y Zhao, X Chen, J Yin, J Qu RNA biology 17 (2), 281-291, 2020 | 47 | 2020 |
| Prediction of small molecule–microRNA associations by sparse learning and heterogeneous graph inference J Yin, X Chen, CC Wang, Y Zhao, YZ Sun Molecular pharmaceutics 16 (7), 3157-3166, 2019 | 37 | 2019 |
| Identification and analysis of human microbe-disease associations by matrix decomposition and label propagation J Qu, Y Zhao, J Yin Frontiers in microbiology 10, 440066, 2019 | 36 | 2019 |
| A novel computational method for the identification of potential miRNA-disease association based on symmetric non-negative matrix factorization and Kronecker regularized least … Y Zhao, X Chen, J Yin Frontiers in genetics 9, 412039, 2018 | 35 | 2018 |
| Drug-pathway association prediction: from experimental results to computational models CC Wang, Y Zhao, X Chen Briefings in bioinformatics 22 (3), bbaa061, 2021 | 33 | 2021 |
| Computational model development of drug-target interaction prediction: a review Q Zhao, H Yu, M Ji, Y Zhao, X Chen Current Protein and Peptide Science 20 (6), 492-494, 2019 | 32 | 2019 |
| Microbes and complex diseases: from experimental results to computational models Y Zhao, CC Wang, X Chen Briefings in Bioinformatics 22 (3), bbaa158, 2021 | 31 | 2021 |
| Prediction of potential miRNA-disease associations using matrix decomposition and label propagation J Qu, X Chen, J Yin, Y Zhao, ZW Li Knowledge-Based Systems 186, 104963, 2019 | 24 | 2019 |
| Identification of miRNA–disease associations via multiple information integration with Bayesian ranking CC Zhu, CC Wang, Y Zhao, M Zuo, X Chen Briefings in Bioinformatics 22 (6), bbab302, 2021 | 17 | 2021 |
| Computational models for self-interacting proteins prediction J Qu, Y Zhao, L Zhang, SB Cai, Z Ming, CC Wang Protein and Peptide Letters 27 (5), 392-399, 2020 | 2 | 2020 |
| LRMDA: using logistic regression and random walk with restart for MiRNA-disease association prediction Z Li, R Nie, Z You, Y Zhao, X Ge, Y Wang Intelligent Computing Theories and Application: 15th International …, 2019 | 2 | 2019 |
