| A computational-based method for predicting drug–target interactions by using stacked autoencoder deep neural network L Wang, ZH You, X Chen, SX Xia, F Liu, X Yan, Y Zhou, KJ Song Journal of Computational Biology 25 (3), 361-373, 2018 | 174 | 2018 |
| Predicting protein–protein interactions from protein sequences by a stacked sparse autoencoder deep neural network YB Wang, ZH You, X Li, TH Jiang, X Chen, X Zhou, L Wang Molecular BioSystems 13 (7), 1336-1344, 2017 | 138 | 2017 |
| Using weighted sparse representation model combined with discrete cosine transformation to predict protein-protein interactions from protein sequence YA Huang, ZH You, X Gao, L Wong, L Wang BioMed research international 2015, 2015 | 119 | 2015 |
| LMTRDA: Using logistic model tree to predict MiRNA-disease associations by fusing multi-source information of sequences and similarities L Wang, ZH You, X Chen, YM Li, YN Dong, LP Li, K Zheng PLoS computational biology 15 (3), e1006865, 2019 | 116 | 2019 |
| An efficient approach based on multi-sources information to predict circRNA–disease associations using deep convolutional neural network L Wang, ZH You, YA Huang, DS Huang, KCC Chan Bioinformatics 36 (13), 4038-4046, 2020 | 114 | 2020 |
| Rfdt: A rotation forest-based predictor for predicting drug-target interactions using drug structure and protein sequence information L Wang, ZH You, X Chen, X Yan, G Liu, W Zhang Current Protein and Peptide Science 19 (5), 445-454, 2018 | 108 | 2018 |
| GCNCDA: a new method for predicting circRNA-disease associations based on graph convolutional network algorithm L Wang, ZH You, YM Li, K Zheng, YA Huang PLOS Computational Biology 16 (5), e1007568, 2020 | 103 | 2020 |
| Predicting protein-protein interactions from matrix-based protein sequence using convolution neural network and feature-selective rotation forest L Wang, HF Wang, SR Liu, X Yan, KJ Song Scientific reports 9 (1), 9848, 2019 | 96 | 2019 |
| MLMDA: a machine learning approach to predict and validate MicroRNA–disease associations by integrating of heterogenous information sources K Zheng, ZH You, L Wang, Y Zhou, LP Li, ZW Li Journal of translational medicine 17, 1-14, 2019 | 82 | 2019 |
| HINGRL: predicting drug–disease associations with graph representation learning on heterogeneous information networks BW Zhao, L Hu, ZH You, L Wang, XR Su Briefings in bioinformatics 23 (1), bbab515, 2022 | 81 | 2022 |
| iCDA-CGR: Identification of circRNA-disease associations based on Chaos Game Representation K Zheng, ZH You, JQ Li, L Wang, ZH Guo, YA Huang PLoS Computational Biology 16 (5), e1007872, 2020 | 64 | 2020 |
| A deep learning method for repurposing antiviral drugs against new viruses via multi-view nonnegative matrix factorization and its application to SARS-CoV-2 X Su, L Hu, Z You, P Hu, L Wang, B Zhao Briefings in bioinformatics 23 (1), bbab526, 2022 | 61 | 2022 |
| Combining high speed ELM learning with a deep convolutional neural network feature encoding for predicting protein-RNA interactions L Wang, ZH You, DS Huang, F Zhou IEEE/ACM transactions on computational biology and bioinformatics 17 (3 …, 2018 | 61 | 2018 |
| Advancing the prediction accuracy of protein-protein interactions by utilizing evolutionary information from position-specific scoring matrix and ensemble classifier L Wang, ZH You, SX Xia, F Liu, X Chen, X Yan, Y Zhou Journal Of Theoretical Biology 418, 105-110, 2017 | 58 | 2017 |
| LDGRNMF: LncRNA-disease associations prediction based on graph regularized non-negative matrix factorization MN Wang, ZH You, L Wang, LP Li, K Zheng Neurocomputing 424, 236-245, 2021 | 57 | 2021 |
| IMS-CDA: prediction of CircRNA-disease associations from the integration of multisource similarity information with deep stacked autoencoder model L Wang, ZH You, JQ Li, YA Huang IEEE transactions on cybernetics 51 (11), 5522-5531, 2020 | 54 | 2020 |
| Biomedical knowledge graph embedding with capsule network for multi-label drug-drug interaction prediction X Su, ZH You, D Huang, L Wang, L Wong, B Ji, B Zhao IEEE Transactions on Knowledge and Data Engineering, 2022 | 53 | 2022 |
| Dbmda: A unified embedding for sequence-based mirna similarity measure with applications to predict and validate mirna-disease associations K Zheng, ZH You, L Wang, Y Zhou, LP Li, ZW Li Molecular Therapy-Nucleic Acids 19, 602-611, 2020 | 52 | 2020 |
| A convolutional neural network using dinucleotide one-hot encoder for identifying DNA N6-methyladenine sites in the rice genome Z Lv, H Ding, L Wang, Q Zou Neurocomputing 422, 214-221, 2021 | 50 | 2021 |
| MGRCDA: Metagraph recommendation method for predicting circRNA–disease association L Wang, ZH You, DS Huang, JQ Li IEEE transactions on cybernetics 53 (1), 67-75, 2021 | 44 | 2021 |
Zhu-Hong YOU（尤著宏）Northwestern Polytechnical University (NPU)Verified email at ms.xjb.ac.cn
