304 results on '"Gao, Ying-Lian"'
Search Results
52. Differentially expressed genes selection via Laplacian regularized low-rank representation method
53. Graph Regularized Non-negative Matrix with L0-Constraints for Selecting Characteristic Genes
54. Application of Graph Regularized Non-negative Matrix Factorization in Characteristic Gene Selection
55. A Two-Stage Sparse Selection Method for Extracting Characteristic Genes
56. Semi-supervised Feature Extraction for RNA-Seq Data Analysis
57. NTBiRW: A Novel Neighbor Model Based on Two-Tier Bi-Random Walk for Predicting Potential Disease-Related Microbes
58. Non-negative low-rank representation with similarity correction for cell type identification in scRNA-seq data
59. BioSTD: A New Tensor Multi-View Framework via Combining Tensor Decomposition and Strong Complementarity Constraint for Analyzing Cancer Omics Data
60. Multi-Kernel Graph Attention Deep Autoencoder for MiRNA-Disease Association Prediction
61. Performance Analysis of Non-negative Matrix Factorization Methods on TCGA Data
62. NPCMF: Nearest Profile-based Collaborative Matrix Factorization method for predicting miRNA-disease associations
63. L2,1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions
64. HSAELDA: Predicting lncRNA-disease associations based on heterogeneous networks and Stacked Autoencoder
65. An integrated Extreme learning machine based on kernel risk-sensitive loss of q-Gaussian and voting mechanism for sample classification
66. Predicting LncRNA-Disease Associations Based on LncRNA-MiRNA-Disease Multilayer Association Network and Bipartite Network Recommendation
67. Tensor Decomposition Based on Global Features and Sparse Structure for Analyzing Cancer Multiomics Data
68. BMPMDA: Prediction of MiRNA-Disease Associations Using a Space Projection Model Based on Block Matrix
69. A new framework for drug–disease association prediction combing light-gated message passing neural network and gated fusion mechanism
70. Ensemble Adaptive Total Variation Graph Regularized NMF for Singlecell RNA-seq Data Analysis
71. Robust Principal Component Analysis Based On Hypergraph Regularization for Sample Clustering and Co-Characteristic Gene Selection
72. NCPLP: A Novel Approach for Predicting Microbe-Associated Diseases With Network Consistency Projection and Label Propagation
73. Tensor decomposition based on the potential low-rank and p-shrinkage generalized threshold algorithm for analyzing cancer multiomics data
74. A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection
75. LDCMFC: Predicting Long Non-coding RNA and Disease Association Using Collaborative Matrix Factorization based on Correntropy
76. Unsupervised Cluster Analysis and Gene Marker Extraction of scRNA-seq Data Based On Non-Negative Matrix Factorization
77. MSF-LRR: Multi-similarity Information Fusion through Low-Rank Representation to Predict Disease-associated Microbes
78. A Simple Review of Sparse Principal Components Analysis
79. Comparison of Non-negative Matrix Factorization Methods for Clustering Genomic Data
80. Adaptive total-variation joint learning model for analyzing single cell RNA seq data
81. Robust Tensor Method Based on Correntropy and Tensor Singular Value Decomposition for Cancer Genomics Data
82. Sparse Hyper-graph Non-negative Matrix Factorization by Maximizing Correntropy
83. Ensemble Adaptive Total Variation Graph Regularized NMF for Singlecell RNA-seq Data Analysis
84. Dual Hyper-Graph Regularized Supervised NMF for Selecting Differentially Expressed Genes and Tumor Classification
85. new framework for drug–disease association prediction combing light-gated message passing neural network and gated fusion mechanism.
86. A Two-Stage Sparse Selection Method for Extracting Characteristic Genes
87. Application of Graph Regularized Non-negative Matrix Factorization in Characteristic Gene Selection
88. Graph Regularized Non-negative Matrix with L0-Constraints for Selecting Characteristic Genes
89. Kernel risk-sensitive mean p-power error based robust extreme learning machine for classification
90. DSTPCA: Double-Sparse Constrained Tensor Principal Component Analysis Method for Feature Selection
91. MSF-LRR: Multi-Similarity Information Fusion Through Low-Rank Representation to Predict Disease-Associated Microbes
92. LDCMFC: Predicting Long Non-Coding RNA and Disease Association Using Collaborative Matrix Factorization Based on Correntropy
93. LWPCMF: Logistic Weighted Profile-Based Collaborative Matrix Factorization for Predicting MiRNA-Disease Associations
94. Multi-Label Fusion Collaborative Matrix Factorization for Predicting LncRNA-Disease Associations
95. Sparse robust graph-regularized non-negative matrix factorization based on correntropy
96. WGRCMF: A Weighted Graph Regularized Collaborative Matrix Factorization Method for Predicting Novel LncRNA-Disease Associations
97. Locally Manifold Non-negative Matrix Factorization Based on Centroid for scRNA-seq Data Analysis
98. MCCMF: Collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations
99. Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification
100. Single-Cell RNA Sequencing Data Clustering by Low-Rank Subspace Ensemble Framework.
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