Graph regularized robust non-negative matrix factorization for clustering and selecting differentially expressed genes. - Na Yu 004; Jin-Xing Liu 001; Ying-Lian Gao; Chun-Hou Zheng 001; Juan Wang 003; Ming-Juan Wu (BIBM, 2017)

Hypergraph regularized NMF by L2, 1-norm for Clustering and Com-abnormal Expression Genes Selection. - Na Yu 004; Ying-Lian Gao; Jin-Xing Liu 001; Juan Wang 003; Junliang Shang (BIBM, 2018)

Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification. - Cui-Na Jiao; Ying-Lian Gao; Na Yu 004; Jin-Xing Liu 001; Lianyong Qi (IEEE J. Biomed. Health Informatics, 2020)

A Semi-Supervised Learning Algorithm for Predicting MiRNA-Disease Association. - Na Yu 004; Zhi-Ping Liu; Rui Gao 006 (BIBM, 2021)

Dual Hyper-Graph Regularized Supervised NMF for Selecting Differentially Expressed Genes and Tumor Classification. - Chuan-Yuan Wang; Na Yu 004; Ming-Juan Wu; Ying-Lian Gao; Jin-Xing Liu 001; Juan Wang 003 (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Correntropy-Based Hypergraph Regularized NMF for Clustering and Feature Selection on Multi-Cancer Integrated Data. - Na Yu 004; Ming-Juan Wu; Jin-Xing Liu 001; Chun-Hou Zheng 001; Yong Xu 001 (IEEE Trans. Cybern., 2021)

Predicting multiple types of MicroRNA-disease associations based on tensor factorization and label propagation. - Na Yu 004; Zhi-Ping Liu; Rui Gao 006 (Comput. Biol. Medicine, 2022)

A Tensor Method Based on Enhanced Tensor Nuclear Norm and Hypergraph Laplacian Regularization for Pan-Cancer Omics Data Analysis. - Na Yu 004; Yusen Zhang 002; Rui Gao 006 (IEEE J. Biomed. Health Informatics, 2023)