| Detecting temporal protein complexes from dynamic protein-protein interaction networks L Ou-Yang, DQ Dai, XL Li, M Wu, XF Zhang, P Yang BMC bioinformatics 15, 1-14, 2014 | 82 | 2014 |
| Recent advances in network-based methods for disease gene prediction SK Ata, M Wu, Y Fang, L Ou-Yang, CK Kwoh, XL Li Briefings in bioinformatics 22 (4), bbaa303, 2021 | 75 | 2021 |
| Determining minimum set of driver nodes in protein-protein interaction networks XF Zhang, L Ou-Yang, Y Zhu, MY Wu, DQ Dai BMC bioinformatics 16, 1-13, 2015 | 73 | 2015 |
| Predicting the impacts of mutations on protein-ligand binding affinity based on molecular dynamics simulations and machine learning methods DD Wang, L Ou-Yang, H Xie, M Zhu, H Yan Computational and structural biotechnology journal 18, 439-454, 2020 | 69 | 2020 |
| A graph regularized generalized matrix factorization model for predicting links in biomedical bipartite networks ZC Zhang, XF Zhang, M Wu, L Ou-Yang, XM Zhao, XL Li Bioinformatics 36 (11), 3474-3481, 2020 | 67 | 2020 |
| Detecting overlapping protein complexes based on a generative model with functional and topological properties XF Zhang, DQ Dai, L Ou-Yang, H Yan BMC bioinformatics 15, 1-15, 2014 | 56 | 2014 |
| Incorporating prior information into differential network analysis using non-paranormal graphical models XF Zhang, L Ou-Yang, H Yan Bioinformatics 33 (16), 2436-2445, 2017 | 51 | 2017 |
| Detecting protein complexes from signed protein-protein interaction networks L Ou-Yang, DQ Dai, XF Zhang IEEE/ACM transactions on computational biology and bioinformatics 12 (6 …, 2015 | 50 | 2015 |
| Differential network analysis from cross-platform gene expression data XF Zhang, L Ou-Yang, XM Zhao, H Yan Scientific reports 6 (1), 34112, 2016 | 48 | 2016 |
| Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization J Huang, M Wu, F Lu, L Ou-Yang, Z Zhu BMC bioinformatics 20, 1-8, 2019 | 40 | 2019 |
| Integrating node embeddings and biological annotations for genes to predict disease-gene associations SK Ata, L Ou-Yang, Y Fang, CK Kwoh, M Wu, XL Li BMC systems biology 12, 31-44, 2018 | 40 | 2018 |
| Self-weighted adaptive structure learning for ASD diagnosis via multi-template multi-center representation F Huang, EL Tan, P Yang, S Huang, L Ou-Yang, J Cao, T Wang, B Lei Medical image analysis 63, 101662, 2020 | 38 | 2020 |
| Graph convolutional network analysis for mild cognitive impairment prediction X Zhao, F Zhou, L Ou-Yang, T Wang, B Lei 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 38 | 2019 |
| EnImpute: imputing dropout events in single-cell RNA-sequencing data via ensemble learning XF Zhang, L Ou-Yang, S Yang, XM Zhao, X Hu, H Yan Bioinformatics 35 (22), 4827-4829, 2019 | 36 | 2019 |
| Protein complex detection via weighted ensemble clustering based on Bayesian nonnegative matrix factorization L Ou-Yang, DQ Dai, XF Zhang PloS one 8 (5), e62158, 2013 | 36 | 2013 |
| RepLong: de novo repeat identification using long read sequencing data R Guo, YR Li, S He, L Ou-Yang, Y Sun, Z Zhu Bioinformatics 34 (7), 1099-1107, 2018 | 34 | 2018 |
| Identifying gene network rewiring by integrating gene expression and gene network data T Xu, L Ou-Yang, X Hu, XF Zhang IEEE/ACM Transactions on Computational Biology and Bioinformatics 15 (6 …, 2018 | 32 | 2018 |
| scTSSR: gene expression recovery for single-cell RNA sequencing using two-side sparse self-representation K Jin, L Ou-Yang, XM Zhao, H Yan, XF Zhang Bioinformatics 36 (10), 3131-3138, 2020 | 30 | 2020 |
| A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks L Ou-Yang, H Yan, XF Zhang BMC bioinformatics 18, 23-34, 2017 | 29 | 2017 |
| T3SEpp: an integrated prediction pipeline for bacterial type III secreted effectors X Hui, Z Chen, M Lin, J Zhang, Y Hu, Y Zeng, X Cheng, L Ou-Yang, M Sun, ... Msystems 5 (4), 10.1128/msystems. 00288-20, 2020 | 28 | 2020 |
Xiao-Fei ZhangSchool of Mathematics and Statistics, Central China Normal UniversityAdresse e-mail validée de mail.ccnu.edu.cn