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 | 248 | 2018 |
Correlation of gut microbiome between ASD children and mothers and potential biomarkers for risk assessment N Li, J Yang, J Zhang, C Liang, Y Wang, B Chen, C Zhao, J Wang, ... Genomics, Proteomics and Bioinformatics 17 (1), 26-38, 2019 | 126 | 2019 |
Dysbiosis of the gut microbiome is associated with thyroid cancer and thyroid nodules and correlated with clinical index of thyroid function J Zhang, F Zhang, C Zhao, Q Xu, C Liang, Y Yang, H Wang, Y Shang, ... Endocrine 64, 564-574, 2019 | 120 | 2019 |
Dysbiosis of the salivary microbiome is associated with non-smoking female lung cancer and correlated with immunocytochemistry markers J Yang, X Mu, Y Wang, D Zhu, J Zhang, C Liang, B Chen, J Wang, C Zhao, ... Frontiers in oncology 8, 520, 2018 | 94 | 2018 |
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 | 91 | 2014 |
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 | 82 | 2015 |
Response of gut microbiota in type 2 diabetes to hypoglycemic agents F Zhang, M Wang, J Yang, Q Xu, C Liang, B Chen, J Zhang, Y Yang, ... Endocrine 66, 485-493, 2019 | 79 | 2019 |
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 | 79 | 2019 |
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 | 79 | 2016 |
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 | 71 | 2017 |
Compositional and functional analysis of the microbiome in tissue and saliva of oral squamous cell carcinoma Z Zhang, J Yang, Q Feng, B Chen, M Li, C Liang, M Li, Z Li, Q Xu, L Zhang, ... Frontiers in Microbiology 10, 1439, 2019 | 70 | 2019 |
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 | 70 | 2018 |
Comprehensive analysis of competitive endogenous RNAs network associated with head and neck squamous cell carcinoma XN Fang, M Yin, H Li, C Liang, C Xu, GW Yang, HX Zhang Scientific Reports 8 (1), 10544, 2018 | 67 | 2018 |
Multi-view feature selection via nonnegative structured graph learning X Bai, L Zhu, C Liang, J Li, X Nie, X Chang Neurocomputing 387, 110-122, 2020 | 60 | 2020 |
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 | 60 | 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 | 59 | 2019 |
NCPCDA: network consistency projection for circRNA–disease association prediction G Li, Y Yue, C Liang, Q Xiao, P Ding, J Luo RSC advances 9 (57), 33222-33228, 2019 | 56 | 2019 |
Inferring probabilistic miRNA–mRNA interaction signatures in cancers: a role-switch approach Y Li, C Liang, KC Wong, K Jin, Z Zhang Nucleic acids research 42 (9), e76-e76, 2014 | 50 | 2014 |
Prediction of LncRNA-disease associations based on network consistency projection G Li, J Luo, C Liang, Q Xiao, P Ding, Y Zhang Ieee Access 7, 58849-58856, 2019 | 47 | 2019 |
KATZMDA: prediction of miRNA-disease associations based on KATZ model Y Qu, H Zhang, C Liang, X Dong Ieee Access 6, 3943-3950, 2017 | 42 | 2017 |