Ying-Lian Gao

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 93

Top Topics

Matrix Factorization

Factorization Method

Differentially Expressed

Top Venues

IEEE J. Biomed. Health Informatics

IEEE ACM Trans. Comput. Biol. Bioinform.

Publications

Cui-Na Jiao, Junliang Shang, Feng Li, Xinchun Cui, Yan-Li Wang, Ying-Lian Gao, Jin-Xing Liu
Diagnosis-Guided Deep Subspace Clustering Association Study for Pathogenetic Markers Identification of Alzheimer's Disease Based on Comparative Atlases. IEEE J. Biomed. Health Informatics 28 (5) (2024)
Jing Jing, Ying-Lian Gao, Yue Gao, Dao-Hui Ge, Chun-Hou Zheng, Jin-Xing Liu
stMCFN: A Multi-view Contrastive Fusion Method for Spatial Domain Identification in Spatial Transcriptomics. ICIC (LNBI 1) (2024)
Dai-Jun Zhang, Ying-Lian Gao, Jing-Xiu Zhao, Chun-Hou Zheng, Jin-Xing Liu
A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection. IEEE Trans. Neural Networks Learn. Syst. 35 (2) (2024)
Cui-Na Jiao, Feng Zhou, Bao-Min Liu, Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao
Multi-Kernel Graph Attention Deep Autoencoder for MiRNA-Disease Association Prediction. IEEE J. Biomed. Health Informatics 28 (2) (2024)
Wen-Yue Kang, Ying-Lian Gao, Ying Wang, Feng Li, Jin-Xing Liu
KFDAE: CircRNA-Disease Associations Prediction Based on Kernel Fusion and Deep Auto-Encoder. IEEE J. Biomed. Health Informatics 28 (5) (2024)
Bao-Min Liu, Ying-Lian Gao, Feng Li, Chun-Hou Zheng, Jin-Xing Liu
SLGCN: Structure-enhanced line graph convolutional network for predicting drug-disease associations. Knowl. Based Syst. 283 (2024)
Cui-Na Jiao, Ying-Lian Gao, Daohui Ge, Junliang Shang, Jin-Xing Liu
Multi-modal imaging genetics data fusion by deep auto-encoder and self-representation network for Alzheimer's disease diagnosis and biomarkers extraction. Eng. Appl. Artif. Intell. 130 (2024)
Wen-Yu Xi, Juan Wang, Yu-Lin Zhang, Jin-Xing Liu, Ying-Lian Gao
LncRNA-disease association prediction method based on heterogeneous information completion and convolutional neural network. CoRR (2024)
Yue Gao, Ying-Lian Gao, Jing Jing, Feng Li, Chun-Hou Zheng, Jin-Xing Liu
A review of recent advances in spatially resolved transcriptomics data analysis. Neurocomputing 603 (2024)
Jin-Xing Liu, Wen-Yu Xi, Ling-Yun Dai, Chun-Hou Zheng, Ying-Lian Gao
Heterogeneous network and graph attention auto-encoder for LncRNA-disease association prediction. CoRR (2024)
Meng-Meng Yin, Ying-Lian Gao, Chun-Hou Zheng, Jin-Xing Liu
NTBiRW: A Novel Neighbor Model Based on Two-Tier Bi-Random Walk for Predicting Potential Disease-Related Microbes. IEEE J. Biomed. Health Informatics 27 (3) (2023)
Ying Wang, Ying-Lian Gao, Juan Wang, Feng Li, Jin-Xing Liu
MSGCA: Drug-Disease Associations Prediction Based on Multi-Similarities Graph Convolutional Autoencoder. IEEE J. Biomed. Health Informatics 27 (7) (2023)
Wen-Yu Xi, Feng Zhou, Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng
LDCMFC: Predicting Long Non-Coding RNA and Disease Association Using Collaborative Matrix Factorization Based on Correntropy. IEEE ACM Trans. Comput. Biol. Bioinform. 20 (3) (2023)
Yue Gao, Dai-Jun Zhang, Cui-Na Jiao, Ying-Lian Gao, Jin-Xing Liu
Spatial Domain Identification Based on Graph Attention Denoising Auto-encoder. ICIC (3) (2023)
Yi Shen, Ying-Lian Gao, Juan Wang, Boxin Guan, Jin-Xing Liu
Identification of Disease-Associated MicroRNAs Via Locality-Constrained Linear Coding-Based Ensemble Learning. J. Comput. Biol. 30 (8) (2023)
Ying Wang, Jin-Xing Liu, Juan Wang, Junliang Shang, Ying-Lian Gao
A Graph Representation Approach Based on Light Gradient Boosting Machine for Predicting Drug-Disease Associations. J. Comput. Biol. 30 (8) (2023)
Wen-Yue Kang, Chun-Hou Zheng, Ying-Lian Gao, Juan Wang, Junliang Shang, Jin-Xing Liu
GRPGAT: Predicting CircRNA-disease Associations Based on Graph Random Propagation Network and Graph Attention Network. BIBM (2023)
Guozheng Zhang, Ying-Lian Gao
BRWMC: Predicting lncRNA-disease associations based on bi-random walk and matrix completion on disease and lncRNA networks. Comput. Biol. Chem. 103 (2023)
Jin-Xing Liu, Meng-Meng Yin, Ying-Lian Gao, Junliang Shang, Chun-Hou Zheng
MSF-LRR: Multi-Similarity Information Fusion Through Low-Rank Representation to Predict Disease-Associated Microbes. IEEE ACM Trans. Comput. Biol. Bioinform. 20 (1) (2023)
Shuang Wang, Jin-Xing Liu, Bao-Min Liu, Ling-Yun Dai, Feng Li, Ying-Lian Gao
MKGSAGE: A Computational Framework via Multiple Kernel Fusion on GraphSAGE for Inferring Potential Disease-Related Microbes. BIBM (2023)
Ying-Lian Gao, Qian Qiao, Juan Wang, Shasha Yuan, Jin-Xing Liu
BioSTD: A New Tensor Multi-View Framework via Combining Tensor Decomposition and Strong Complementarity Constraint for Analyzing Cancer Omics Data. IEEE J. Biomed. Health Informatics 27 (10) (2023)
Yi-Ming Wang, Xiang-Zhen Kong, Boxin Guan, Chun-Hou Zheng, Ying-Lian Gao
Identify Complex Higher-Order Associations Between Alzheimer's Disease Genes and Imaging Markers Through Improved Adaptive Sparse Multi-view Canonical Correlation Analysis. ICIC (3) (2023)
Jin-Xing Liu, Dai-Jun Zhang, Jing-Xiu Zhao, Chun-Hou Zheng, Ying-Lian Gao
Non-Negative Low-Rank Representation With Similarity Correction for Cell Type Identification in scRNA-Seq Data. IEEE ACM Trans. Comput. Biol. Bioinform. 20 (6) (2023)
Xu-Ran Dou, Wen-Yu Xi, Tian-Ru Wu, Cui-Na Jiao, Jin-Xing Liu, Ying-Lian Gao
LANCMDA: Predicting MiRNA-Disease Associations via LightGBM with Attributed Network Construction. ICIC (3) (2023)
Chuan-Yuan Wang, Ying-Lian Gao, Xiang-Zhen Kong, Jin-Xing Liu, Chun-Hou Zheng
Unsupervised Cluster Analysis and Gene Marker Extraction of scRNA-seq Data Based On Non-Negative Matrix Factorization. IEEE J. Biomed. Health Informatics 26 (1) (2022)
Zhi-Yuan Li, Ying-Lian Gao, Zhen-Xin Niu, Sha-Sha Yuan, Chun-Hou Zheng, Jin-Xing Liu
An integrated Extreme learning machine based on kernel risk-sensitive loss of q-Gaussian and voting mechanism for sample classification. BIBM (2022)
Hang-Jin Yang, Yuxia Lei, Juan Wang, Xiang-Zhen Kong, Jin-Xing Liu, Ying-Lian Gao
Tensor decomposition based on the potential low-rank and p-shrinkage generalized threshold algorithm for analyzing cancer multiomics data. J. Bioinform. Comput. Biol. 20 (2) (2022)
Chuan-Yuan Wang, Ying-Lian Gao, Jin-Xing Liu, Xiang-Zhen Kong, Chun-Hou Zheng
Single-Cell RNA Sequencing Data Clustering by Low-Rank Subspace Ensemble Framework. IEEE ACM Trans. Comput. Biol. Bioinform. 19 (2) (2022)
Meng-Meng Yin, Ying-Lian Gao, Junliang Shang, Chun-Hou Zheng, Jin-Xing Liu
Multi-similarity fusion-based label propagation for predicting microbes potentially associated with diseases. Future Gener. Comput. Syst. 134 (2022)
Bao-Min Liu, Ying-Lian Gao, Dai-Jun Zhang, Feng Zhou, Juan Wang, Chun-Hou Zheng, Jin-Xing Liu
A new framework for drug-disease association prediction combing light-gated message passing neural network and gated fusion mechanism. Briefings Bioinform. 23 (6) (2022)
Yi Shen, Ying-Lian Gao, Shu-Zhen Li, Boxin Guan, Jin-Xing Liu
A Locality-Constrained Linear Coding-Based Ensemble Learning Framework for Predicting Potentially Disease-Associated MiRNAs. ISBRA (2022)
Wen-Yu Xi, Qian-Qian Ren, Jin-Xing Liu, Ying-Lian Gao
HSAELDA: Predicting lncRNA-disease associations based on heterogeneous networks and Stacked Autoencoder. BIBM (2022)
Meng-Meng Yin, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Chun-Hou Zheng
NCPLP: A Novel Approach for Predicting Microbe-Associated Diseases With Network Consistency Projection and Label Propagation. IEEE Trans. Cybern. 52 (6) (2022)
Guo-Zheng Zhang, Shu-Zhen Li, Xu-Ran Dou, Junliang Shang, Qian-Qian Ren, Ying-Lian Gao
Predicting LncRNA-Disease Associations Based on LncRNA-MiRNA-Disease Multilayer Association Network and Bipartite Network Recommendation. BIBM (2022)
Ying-Lian Gao, Ming-Juan Wu, Jin-Xing Liu, Chun-Hou Zheng, Juan Wang
Robust Principal Component Analysis Based On Hypergraph Regularization for Sample Clustering and Co-Characteristic Gene Selection. IEEE ACM Trans. Comput. Biol. Bioinform. 19 (4) (2022)
Ying Wang, Ying-Lian Gao, Juan Wang, Junliang Shang, Jin-Xing Liu
MLMVFE: A Machine Learning Approach Based on Muli-view Features Extraction for Drug-Disease Associations Prediction. ISBRA (2022)
Liang-Rui Ren, Ying-Lian Gao, Junliang Shang, Jin-Xing Liu
Kernel risk-sensitive mean p-power error based robust extreme learning machine for classification. Int. J. Mach. Learn. Cybern. 13 (1) (2022)
Chuan-Yuan Wang, Na Yu, Ming-Juan Wu, Ying-Lian Gao, Jin-Xing Liu, Juan Wang
Dual Hyper-Graph Regularized Supervised NMF for Selecting Differentially Expressed Genes and Tumor Classification. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (6) (2021)
Chuan-Yuan Wang, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Junliang Shang
Sparse robust graph-regularized non-negative matrix factorization based on correntropy. J. Bioinform. Comput. Biol. 19 (1) (2021)
Jin-Xing Liu, Zhen Cui, Ying-Lian Gao, Xiang-Zhen Kong
WGRCMF: A Weighted Graph Regularized Collaborative Matrix Factorization Method for Predicting Novel LncRNA-Disease Associations. IEEE J. Biomed. Health Informatics 25 (1) (2021)
Yue Hu, Jin-Xing Liu, Ying-Lian Gao, Junliang Shang
DSTPCA: Double-Sparse Constrained Tensor Principal Component Analysis Method for Feature Selection. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (4) (2021)
Ming-Ming Gao, Zhen Cui, Ying-Lian Gao, Juan Wang, Jin-Xing Liu
Multi-Label Fusion Collaborative Matrix Factorization for Predicting LncRNA-Disease Associations. IEEE J. Biomed. Health Informatics 25 (3) (2021)
Ying-Lian Gao, Meng-Meng Yin, Jin-Xing Liu, Junliang Shang, Chun-Hou Zheng
MKL-LP: Predicting Disease-Associated Microbes with Multiple-Similarity Kernel Learning-Based Label Propagation. ISBRA (2021)
Qian Qiao, Ying-Lian Gao, Shasha Yuan, Jin-Xing Liu
Robust Tensor Method Based on Correntropy and Tensor Singular Value Decomposition for Cancer Genomics Data. BIBM (2021)
Dai-Jun Zhang, Jing-Xiu Zhao, Jin-Xing Liu, Ying-Lian Gao
Adaptive total-variation joint learning model for analyzing single cell RNA seq data. BIBM (2021)
Jin-Xing Liu, Ming-Ming Gao, Zhen Cui, Ying-Lian Gao, Feng Li
DSCMF: prediction of LncRNA-disease associations based on dual sparse collaborative matrix factorization. BMC Bioinform. (3) (2021)
Cui-Na Jiao, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Chun-Hou Zheng, Xianzi Yu
Sparse Hyper-graph Non-negative Matrix Factorization by Maximizing Correntropy. BIBM (2021)
Liang-Rui Ren, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Chun-Hou Zheng
Kernel Risk-Sensitive Loss based Hyper-graph Regularized Robust Extreme Learning Machine and Its Semi-supervised Extension for Classification. Knowl. Based Syst. 227 (2021)
Meng-Meng Yin, Zhen Cui, Ming-Ming Gao, Jin-Xing Liu, Ying-Lian Gao
LWPCMF: Logistic Weighted Profile-Based Collaborative Matrix Factorization for Predicting MiRNA-Disease Associations. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (3) (2021)
Zhen-Xin Niu, Liang-Rui Ren, Rong Zhu, Xiang-Zhen Kong, Ying-Lian Gao, Jin-Xing Liu
Extreme Learning Machine Based on Double Kernel Risk-Sensitive Loss for Cancer Samples Classification. ICIC (2) (2021)
Cui-Na Jiao, Ying-Lian Gao, Na Yu, Jin-Xing Liu, Lianyong Qi
Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification. IEEE J. Biomed. Health Informatics 24 (10) (2020)
Zhen Cui, Jin-Xing Liu, Ying-Lian Gao, Rong Zhu, Shasha Yuan
LncRNA-Disease Associations Prediction Using Bipartite Local Model With Nearest Profile-Based Association Inferring. IEEE J. Biomed. Health Informatics 24 (5) (2020)
Yao Lu, Ying-Lian Gao, Pei-Yong Li, Jin-Xing Liu
A multi-view classification and feature selection method via sparse low-rank regression analysis. Int. J. Data Min. Bioinform. 24 (2) (2020)
Liang-Rui Ren, Ying-Lian Gao, Jin-Xing Liu, Rong Zhu, Xiang-Zhen Kong
-Extreme Learning Machine: An Efficient Robust Classifier for Tumor Classification. Comput. Biol. Chem. 89 (2020)
Tianru Wu, Meng-Meng Yin, Cui-Na Jiao, Ying-Lian Gao, Xiang-Zhen Kong, Jin-Xing Liu
MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations. BMC Bioinform. 21 (1) (2020)
Ming-Juan Wu, Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng, Juan Wang
Integrative Hypergraph Regularization Principal Component Analysis for Sample Clustering and Co-Expression Genes Network Analysis on Multi-Omics Data. IEEE J. Biomed. Health Informatics 24 (6) (2020)
Liang-Rui Ren, Ying-Lian Gao, Jin-Xing Liu, Junliang Shang, Chun-Hou Zheng
Correntropy induced loss based sparse robust graph regularized extreme learning machine for cancer classification. BMC Bioinform. 21 (1) (2020)
Liang-Rui Ren, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Chun-Hou Zheng
Robust Graph Regularized Extreme Learning Machine Auto Encoder and Its Application to Single-Cell Samples Classification. ICIC (2) (2020)
Chuan-Yuan Wang, Ying-Lian Gao, Cui-Na Jiao, Jin-Xing Liu, Chunhou Zheng, Xiang-Zhen Kong
Locally Manifold Non-negative Matrix Factorization Based on Centroid for scRNA-seq Data Analysis. BIBM (2020)
Meng-Meng Yin, Zhen Cui, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong
DSNPCMF: Predicting MiRNA-Disease Associations with Collaborative Matrix Factorization Based on Double Sparse and Nearest Profile. IDMB (2019)
Ming-Ming Gao, Zhen Cui, Ying-Lian Gao, Feng Li, Jin-Xing Liu
Dual Sparse Collaborative Matrix Factorization Method Based on Gaussian Kernel Function for Predicting LncRNA-Disease Associations. ICIC (3) (2019)
Chun-Mei Feng, Yong Xu, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng
Supervised Discriminative Sparse PCA for Com-Characteristic Gene Selection and Tumor Classification on Multiview Biological Data. CoRR (2019)
Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang, Ling-Yun Dai
The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method. BMC Bioinform. 20 (1) (2019)
Ying-Lian Gao, Zhen Cui, Jin-Xing Liu, Juan Wang, Chun-Hou Zheng
NPCMF: Nearest Profile-based Collaborative Matrix Factorization method for predicting miRNA-disease associations. BMC Bioinform. 20 (1) (2019)
Ying-Lian Gao, Mi-Xiao Hou, Jin-Xing Liu, Xiang-Zhen Kong
An Integrated Graph Regularized Non-Negative Matrix Factorization Model for Gene Co-Expression Network Analysis. IEEE Access 7 (2019)
Zhen Cui, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Juan Wang
RCMF: a robust collaborative matrix factorization method to predict miRNA-disease associations. BMC Bioinform. (25) (2019)
Yue Hu, Jin-Xing Liu, Ying-Lian Gao, Shengjun Li, Juan Wang
Differentially Expressed Genes Extracted by the Tensor Robust Principal Component Analysis (TRPCA) Method. Complex. 2019 (2019)
Chun-Mei Feng, Yong Xu, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng
Supervised Discriminative Sparse PCA for Com-Characteristic Gene Selection and Tumor Classification on Multiview Biological Data. IEEE Trans. Neural Networks Learn. Syst. 30 (10) (2019)
Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Shasha Yuan
L2, 1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions. BMC Bioinform. (8) (2019)
Mi-Xiao Hou, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Xiang-Zhen Kong, Junliang Shang
Network analysis based on low-rank method for mining information on integrated data of multi-cancers. Comput. Biol. Chem. 78 (2019)
Yong-Jing Hao, Ying-Lian Gao, Mi-Xiao Hou, Ling-Yun Dai, Jin-Xing Liu
Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection. Complex. 2019 (2019)
Jin-Xing Liu, Dong Wang, Ying-Lian Gao, Chun-Hou Zheng, Yong Xu, Jiguo Yu
Regularized Non-Negative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Samples: A Survey. IEEE ACM Trans. Comput. Biol. Bioinform. 15 (3) (2018)
Mi-Xiao Hou, Jin-Xing Liu, Junliang Shang, Ying-Lian Gao, Xiang-Zhen Kong, Ling-Yun Dai
Performance Analysis of Non-negative Matrix Factorization Methods on TCGA Data. ICIC (2) (2018)
Na Yu, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang
Hypergraph regularized NMF by L2, 1-norm for Clustering and Com-abnormal Expression Genes Selection. BIBM (2018)
Na Yu, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Juan Wang, Ming-Juan Wu
Graph regularized robust non-negative matrix factorization for clustering and selecting differentially expressed genes. BIBM (2017)
Jin-Xing Liu, Dong Wang, Ying-Lian Gao, Chun-Hou Zheng, Junliang Shang, Feng Liu, Yong Xu
-norm-constraint-based semi-supervised feature extraction for RNA-Seq data analysis. Neurocomputing 228 (2017)
Ming-Juan Wu, Jin-Xing Liu, Ying-Lian Gao, Xiangzhen Kong, Chun-Mei Feng
Feature selection and clustering via robust graph-laplacian PCA based on capped L1-norm. BIBM (2017)
Yaxuan Wang, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Ling-Yun Dai
Low-rank representation regularized by L2, 1-norm for identifying differentially expressed genes. BIBM (2017)
Xiu-Xiu Xu, Ying-Lian Gao, Jin-Xing Liu, Yaxuan Wang, Ling-Yun Dai, Xiang-Zhen Kong, Shasha Yuan
A novel low-rank representation method for identifying differentially expressed genes. Int. J. Data Min. Bioinform. 19 (3) (2017)
Jin-Xing Liu, Dong-Qin Wang, Chun-Hou Zheng, Ying-Lian Gao, Sha-Sha Wu, Junliang Shang
Identifying drug-pathway association pairs based on L2, 1-integrative penalized matrix decomposition. BMC Syst. Biol. 11 (6) (2017)
Yaxuan Wang, Jin-Xing Liu, Ying-Lian Gao, Xiangzhen Kong, Chun-Hou Zheng, Yong Du
Differentially expressed genes selection via Truncated Nuclear Norm Regularization. BIBM (2016)
Chun-Mei Feng, Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng, Shengjun Li, Dong Wang
A Simple Review of Sparse Principal Components Analysis. ICIC (2) (2016)
Chun-Mei Feng, Jin-Xing Liu, Ying-Lian Gao, Juan Wang, Dong-Qin Wang, Yong Du
A graph-Laplacian PCA based on L1/2-norm constraint for characteristic gene selection. BIBM (2016)
Yaxuan Wang, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Junliang Shang
Differentially expressed genes selection via Laplacian regularized low-rank representation method. Comput. Biol. Chem. 65 (2016)
Jin-Xing Liu, Yong Xu, Ying-Lian Gao, Chun-Hou Zheng, Dong Wang, Qi Zhu
A Class-Information-Based Sparse Component Analysis Method to Identify Differentially Expressed Genes on RNA-Seq Data. IEEE ACM Trans. Comput. Biol. Bioinform. 13 (2) (2016)
Dong-Qin Wang, Chun-Hou Zheng, Ying-Lian Gao, Jin-Xing Liu, Sha-Sha Wu, Junliang Shang
L21-iPaD: An efficient method for drug-pathway association pairs inference. BIBM (2016)
Mi-Xiao Hou, Ying-Lian Gao, Jin-Xing Liu, Junliang Shang, Chun-Hou Zheng
Comparison of Non-negative Matrix Factorization Methods for Clustering Genomic Data. ICIC (2) (2016)
Yao Lu, Ying-Lian Gao, Jin-Xing Liu, Chang-Gang Wen, Yaxuan Wang, Jiguo Yu
Characteristic gene selection via L2, 1-norm Sparse Principal Component Analysis. BIBM (2016)
Dong Wang, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Yong Xu
Characteristic Gene Selection Based on Robust Graph Regularized Non-Negative Matrix Factorization. IEEE ACM Trans. Comput. Biol. Bioinform. 13 (6) (2016)
Chun-Xia Ma, Ying-Lian Gao, Dong Wang, Jian Liu, Jin-Xing Liu
Graph Regularized Non-negative Matrix with L0-Constraints for Selecting Characteristic Genes. ICIC (2) (2015)
Jin-Xing Liu, Yong Xu, Ying-Lian Gao, Dong Wang, Chun-Hou Zheng, Junliang Shang
Semi-supervised Feature Extraction for RNA-Seq Data Analysis. ICIC (3) (2015)
Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng, Shengjun Li, Yuxia Lei
A Two-Stage Sparse Selection Method for Extracting Characteristic Genes. ICIC (2) (2015)
Dong Wang, Ying-Lian Gao, Jin-Xing Liu, Jiguo Yu, Chang-Gang Wen
Application of Graph Regularized Non-negative Matrix Factorization in Characteristic Gene Selection. ICIC (2) (2015)