| Matrix factorization-based data fusion for the prediction of lncRNA–disease associations G Fu, J Wang, C Domeniconi, G Yu Bioinformatics 34 (9), 1529-1537, 2018 | 145 | 2018 |
| Protein-Protein Interactions Prediction based on Ensemble Deep Neural Networks L Zhang, G Yu, D Xia, J Wang Neurocomputing 324, 10-19, 2019 | 107 | 2019 |
| Incomplete multi-view weak-label learning. Q Tan, G Yu, C Domeniconi, J Wang, Z Zhang Ijcai, 2703-2709, 2018 | 75 | 2018 |
| A literature review of gene function prediction by modeling gene ontology Y Zhao, J Wang, J Chen, X Zhang, M Guo, G Yu Frontiers in genetics 11, 400, 2020 | 61 | 2020 |
| Feature-induced partial multi-label learning G Yu, X Chen, C Domeniconi, J Wang, Z Li, Z Zhang, X Wu 2018 IEEE International Conference on Data Mining (ICDM), 1398-1403, 2018 | 61 | 2018 |
| BRWLDA: bi-random walks for predicting lncRNA-disease associations G Yu, G Fu, C Lu, Y Ren, J Wang Oncotarget 8 (36), 60429, 2017 | 61 | 2017 |
| Activehne: Active heterogeneous network embedding X Chen, G Yu, J Wang, C Domeniconi, Z Li, X Zhang arXiv preprint arXiv:1905.05659, 2019 | 55 | 2019 |
| Ranking-based deep cross-modal hashing X Liu, G Yu, C Domeniconi, J Wang, Y Ren, M Guo Proceedings of the AAAI conference on artificial intelligence 33 (01), 4400-4407, 2019 | 53 | 2019 |
| Multi-label co-training Y Xing, G Yu, C Domeniconi, J Wang, Z Zhang Proceedings of the 27th international joint conference on artificial …, 2018 | 52 | 2018 |
| Multi-scale Agent-based Modeling on melanoma and its related angiogenesis analysis J Wang, L Zhang, C Jing, G Ye, H Wu, H Miao, Y Wu, X Zhou Theoretical Biology and Medical Modelling 10, 41, 2013 | 52 | 2013 |
| Clustering cancer gene expression data by projective clustering ensemble X Yu, G Yu, J Wang PloS one 12 (2), e0171429, 2017 | 50 | 2017 |
| Multi-view multiple clusterings using deep matrix factorization S Wei, J Wang, G Yu, C Domeniconi, X Zhang Proceedings of the AAAI conference on artificial intelligence 34 (04), 6348-6355, 2020 | 45 | 2020 |
| BMC3C: binning metagenomic contigs using codon usage, sequence composition and read coverage G Yu, Y Jiang, J Wang, H Zhang, H Luo Bioinformatics 34 (24), 4172-4179, 2018 | 43 | 2018 |
| Predicting protein function via semantic integration of multiple networks G Yu, G Fu, J Wang, H Zhu IEEE/ACM transactions on computational biology and bioinformatics 13 (2 …, 2015 | 43 | 2015 |
| Gene function prediction based on gene ontology hierarchy preserving hashing Y Zhao, G Fu, J Wang, M Guo, G Yu Genomics 111 (3), 334-342, 2019 | 42 | 2019 |
| Multi-view multiple clustering S Yao, G Yu, J Wang, C Domeniconi, X Zhang arXiv preprint arXiv:1905.05053, 2019 | 40 | 2019 |
| Protein-protein interactions prediction using a novel local conjoint triad descriptor of amino acid sequences J Wang, L Zhang, L Jia, Y Ren, G Yu International Journal of Molecular Sciences 18 (11), 2373, 2017 | 39 | 2017 |
| Semi-supervised multi-label classification using incomplete label information Q Tan, Y Yu, G Yu, J Wang Neurocomputing 260, 192-202, 2017 | 39 | 2017 |
| NegGOA: negative GO annotations selection using ontology structure G Fu, J Wang, B Yang, G Yu Bioinformatics 32 (19), 2996-3004, 2016 | 39 | 2016 |
| NewGOA: Predicting new GO annotations of proteins by bi-random walks on a hybrid graph G Yu, G Fu, J Wang, Y Zhao IEEE/ACM transactions on computational biology and bioinformatics 15 (4 …, 2017 | 33 | 2017 |
Guoxian Yu(余国先)Professor, School of Software, Shandong University, Jinan, ChinaVerified email at sdu.edu.cn
