| Feature selection in machine learning: A new perspective J Cai, J Luo, S Wang, S Yang Neurocomputing 300, 70-79, 2018 | 1581 | 2018 |
| A graph regularized non-negative matrix factorization method for identifying microRNA-disease associations Q Xiao, J Luo, C Liang, J Cai, P Ding Bioinformatics 34 (2), 239-248, 2018 | 222 | 2018 |
| A novel approach for predicting microRNA-disease associations by unbalanced bi-random walk on heterogeneous network J Luo, Q Xiao Journal of biomedical informatics 66, 194-203, 2017 | 95 | 2017 |
| Mirsynergy: detecting synergistic miRNA regulatory modules by overlapping neighbourhood expansion Y Li, C Liang, KC Wong, J Luo, Z Zhang Bioinformatics 30 (18), 2627-2635, 2014 | 88 | 2014 |
| NTSHMDA: prediction of human microbe-disease association based on random walk by integrating network topological similarity J Luo, Y Long IEEE/ACM transactions on computational biology and bioinformatics 17 (4 …, 2018 | 80 | 2018 |
| A novel method to detect functional microRNA regulatory modules by bicliques merging C Liang, Y Li, J Luo IEEE/ACM transactions on computational biology and bioinformatics 13 (3 …, 2015 | 80 | 2015 |
| Multi-view manifold regularized learning-based method for prioritizing candidate disease miRNAs Q Xiao, J Dai, J Luo, H Fujita Knowledge-Based Systems 175, 118-129, 2019 | 79 | 2019 |
| Predicting human microbe–drug associations via graph convolutional network with conditional random field Y Long, M Wu, CK Kwoh, J Luo, X Li Bioinformatics 36 (19), 4918-4927, 2020 | 76 | 2020 |
| Identification of essential proteins based on a new combination of local interaction density and protein complexes J Luo, Y Qi PloS one 10 (6), e0131418, 2015 | 75 | 2015 |
| Collective prediction of disease-associated miRNAs based on transduction learning J Luo, P Ding, C Liang, B Cao, X Chen IEEE/ACM transactions on computational biology and bioinformatics 14 (6 …, 2016 | 74 | 2016 |
| Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs C Liang, S Yu, J Luo PLoS computational biology 15 (4), e1006931, 2019 | 72 | 2019 |
| Multi-view multichannel attention graph convolutional network for miRNA–disease association prediction X Tang, J Luo, C Shen, Z Lai Briefings in bioinformatics 22 (6), bbab174, 2021 | 64 | 2021 |
| Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity G Li, J Luo, Q Xiao, C Liang, P Ding Journal of biomedical informatics 82, 169-177, 2018 | 63 | 2018 |
| Computational prediction of human disease-associated circRNAs based on manifold regularization learning framework Q Xiao, J Luo, J Dai IEEE journal of biomedical and health informatics 23 (6), 2661-2669, 2019 | 62 | 2019 |
| Predicting microrna-disease associations using network topological similarity based on deepwalk G Li, J Luo, Q Xiao, C Liang, P Ding, B Cao Ieee Access 5, 24032-24039, 2017 | 56 | 2017 |
| MCLPMDA: A novel method for mi RNA‐disease association prediction based on matrix completion and label propagation SP Yu, C Liang, Q Xiao, GH Li, PJ Ding, JW Luo Journal of cellular and molecular medicine 23 (2), 1427-1438, 2019 | 55 | 2019 |
| Predicting MicroRNA-disease associations using Kronecker regularized least squares based on heterogeneous omics data J Luo, Q Xiao, C Liang, P Ding Ieee Access 5, 2503-2513, 2017 | 54 | 2017 |
| Protein functional class prediction using global encoding of amino acid sequence X Li, B Liao, Y Shu, Q Zeng, J Luo Journal of theoretical biology 261 (2), 290-293, 2009 | 52 | 2009 |
| Prioritization of potential candidate disease genes by topological similarity of protein–protein interaction network and phenotype data J Luo, S Liang Journal of biomedical informatics 53, 229-236, 2015 | 51 | 2015 |
| Predicting human microbe–disease associations via graph attention networks with inductive matrix completion Y Long, J Luo, Y Zhang, Y Xia Briefings in bioinformatics 22 (3), bbaa146, 2021 | 46 | 2021 |
Chee Keong KWOHNanyang Technological UniversityGeverifieerd e-mailadres voor ntu.edu.sg
