[1] Youlin Zhan, Jiahan Liu, Le Ou-Yang*, scMIC: A Deep Multi-Level Information Fusion Framework for Clustering Single-Cell Multi-Omics Data, IEEE Journal of Biomedical and Health Informatics, 27(12): 6121-6132, 2023.
[2] Zerun Lin, Le Ou-Yang*, Inferring gene regulatory networks from single-cell gene expression data via deep multi-view contrastive learning, Briefings in Bioinformatics, 24(1): bbac586, 2023.
[3] Youlin Zhan, Jiahan Liu, Min Wu, Chris Soon Heng Tan, Xiaoli Li, Le Ou-Yang*, A partially shared joint clustering framework for detecting protein complexes from multiple state-specific signed interaction networks, Computers in Biology and Medicine, 159: 106936, 2023.
[4] Le Ou-Yang, Fan Lu, Zi-Chao Zhang, Min Wu, Matrix factorization for biomedical link prediction and scRNA-seq data imputation: an empirical survey, Briefings in Bioinformatics, 2022, 23(1): bbab479.
[5] Guanhua Zou, Yilong Lin, Tianyang Han, Le Ou-Yang*, DEMOC: a deep embedded multi-omics learning approach for clustering single-cell CITE-seq data, Briefings in Bioinformatics, 2022, 23(5): bbac347.
[6] Wenhui Wu, Yujie Chen, Ran Wang, Le Ou-Yang*, Self-representative kernel concept factorization, Knowledge-Based Systems, 2023, 259: 110051.
[7] Le Ou-Yang, Dehan Cai, Xiao-Fei Zhang, Hong Yan, WDNE: an integrative graphical model for inferring differential networks from multi-platform gene expression data with missing values, Briefings in Bioinformatics, 2021, 22(6): bbab086.
[8] Le Ou-Yang, Xiao-Fei Zhang, Hong Yan, Sparse regularized low-rank tensor regression with applications in genomic data analysis. Pattern Recognition, 2020, 107: 107516.
[9] Xiao-Fei Zhang, Le Ou-Yang*, Ting Yan, Xiaohua Hu, Hong Yan, A joint graphical model for inferring gene networks across multiple subpopulations and data types, IEEE Transactions on Cybernetics, 2021, 51(2): 1043-1055.
[10] Zi-Chao Zhang, Xiao-Fei Zhang, Min Wu, Le Ou-Yang*, Xing-Ming Zhao, Xiao-Li Li, A Graph Regularized Generalized Matrix Factorization Model for Predicting Links in Biomedical Bipartite Networks, Bioinformatics, 2020, 36(11): 3474-3481.
[11] Le Ou-Yang, Xiao-Fei Zhang*, Xiaohua Hu, Hong Yan, Differential network analysis via weighted fused conditional Gaussian graphical model, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, 17(6): 2162 - 2169
[12] Xiao-Fei Zhang, Le Ou-Yang*, Shuo Yang, Xing-Ming Zhao, Xiaohua Hu, Hong Yan, EnImpute: imputing dropout events in single cell RNA sequencing data via ensemble learning, Bioinformatics, 2019, 35(22): 4827-4829.
[13] Xiao-Fei Zhang, Le Ou-Yang*, Shuo Yang, Xiaohua Hu, Hong Yan, DiffNetFDR: Differential network analysis with false discovery rate control, Bioinformatics, 2019,35(17): 3184-3186.
[14] Le Ou-Yang, Xiao-Fei Zhang, Xing-Ming Zhao, Debby D Wang, Fu Lee Wang, Baiying Lei, Hong Yan, Joint Learning of Multiple Differential Networks With Latent Variables, IEEE Transactions on Cybernetics, 2019, 49(9): 3494-3506.
[15] Jiang Huang, Min Wu, Fan Lu, Le Ou-Yang*, Zexuan Zhu, Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization, BMC Bioinformatics,2019, 20(19): 657.
[16] Yuanxiao Chen, Xiao-Fei Zhang, Le Ou-Yang*, Inferring cancer common and specific gene networks via multi-layer joint graphical model, Computational and Structural Biotechnology Journal, 2023, 21: 974-990.
[17] Zerun Lin, Yuhan Zhang, Lixin Duan, Le Ou-Yang*, Peilin Zhao*, MoVAE: A Variational AutoEncoder for Molecular Graph Generation, Proceedings of the 2023 SIAM International Conference on Data Mining (SDM), 2023: 514-522.
[18] Xiao-Fei Zhang, Le Ou-Yang*, Shuo Yang, Xiaohua Hu, Hong Yan,, DiffGraph: An R package for identifying gene network rewiring using differential graphical models, Bioinformatics, 34.9 (2018): 1571-1573.