Ying-Lian Gao
Orcid: 0000-0003-0483-5622
According to our database1,
Ying-Lian Gao
authored at least 85 papers
between 2015 and 2024.
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Bibliography
2024
A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection.
IEEE Trans. Neural Networks Learn. Syst., February, 2024
Multi-Kernel Graph Attention Deep Autoencoder for MiRNA-Disease Association Prediction.
IEEE J. Biomed. Health Informatics, February, 2024
SLGCN: Structure-enhanced line graph convolutional network for predicting drug-disease associations.
Knowl. Based Syst., January, 2024
2023
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, October, 2023
A Graph Representation Approach Based on Light Gradient Boosting Machine for Predicting Drug-Disease Associations.
J. Comput. Biol., August, 2023
Identification of Disease-Associated MicroRNAs Via Locality-Constrained Linear Coding-Based Ensemble Learning.
J. Comput. Biol., August, 2023
MSGCA: Drug-Disease Associations Prediction Based on Multi-Similarities Graph Convolutional Autoencoder.
IEEE J. Biomed. Health Informatics, July, 2023
BRWMC: Predicting lncRNA-disease associations based on bi-random walk and matrix completion on disease and lncRNA networks.
Comput. Biol. Chem., April, 2023
NTBiRW: A Novel Neighbor Model Based on Two-Tier Bi-Random Walk for Predicting Potential Disease-Related Microbes.
IEEE J. Biomed. Health Informatics, March, 2023
LDCMFC: Predicting Long Non-Coding RNA and Disease Association Using Collaborative Matrix Factorization Based on Correntropy.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
Non-Negative Low-Rank Representation With Similarity Correction for Cell Type Identification in scRNA-Seq Data.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
MSF-LRR: Multi-Similarity Information Fusion Through Low-Rank Representation to Predict Disease-Associated Microbes.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
Identify Complex Higher-Order Associations Between Alzheimer's Disease Genes and Imaging Markers Through Improved Adaptive Sparse Multi-view Canonical Correlation Analysis.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023
LANCMDA: Predicting MiRNA-Disease Associations via LightGBM with Attributed Network Construction.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023
MKGSAGE: A Computational Framework via Multiple Kernel Fusion on GraphSAGE for Inferring Potential Disease-Related Microbes.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
GRPGAT: Predicting CircRNA-disease Associations Based on Graph Random Propagation Network and Graph Attention Network.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
2022
Unsupervised Cluster Analysis and Gene Marker Extraction of scRNA-seq Data Based On Non-Negative Matrix Factorization.
IEEE J. Biomed. Health Informatics, 2022
NCPLP: A Novel Approach for Predicting Microbe-Associated Diseases With Network Consistency Projection and Label Propagation.
IEEE Trans. Cybern., 2022
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
Robust Principal Component Analysis Based On Hypergraph Regularization for Sample Clustering and Co-Characteristic Gene Selection.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
Kernel risk-sensitive mean p-power error based robust extreme learning machine for classification.
Int. J. Mach. Learn. Cybern., 2022
Tensor decomposition based on the potential low-rank and p-shrinkage generalized threshold algorithm for analyzing cancer multiomics data.
J. Bioinform. Comput. Biol., 2022
Multi-similarity fusion-based label propagation for predicting microbes potentially associated with diseases.
Future Gener. Comput. Syst., 2022
A new framework for drug-disease association prediction combing light-gated message passing neural network and gated fusion mechanism.
Briefings Bioinform., 2022
MLMVFE: A Machine Learning Approach Based on Muli-view Features Extraction for Drug-Disease Associations Prediction.
Proceedings of the Bioinformatics Research and Applications - 18th International Symposium, 2022
A Locality-Constrained Linear Coding-Based Ensemble Learning Framework for Predicting Potentially Disease-Associated MiRNAs.
Proceedings of the Bioinformatics Research and Applications - 18th International Symposium, 2022
Predicting LncRNA-Disease Associations Based on LncRNA-MiRNA-Disease Multilayer Association Network and Bipartite Network Recommendation.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
HSAELDA: Predicting lncRNA-disease associations based on heterogeneous networks and Stacked Autoencoder.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
An integrated Extreme learning machine based on kernel risk-sensitive loss of q-Gaussian and voting mechanism for sample classification.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
2021
WGRCMF: A Weighted Graph Regularized Collaborative Matrix Factorization Method for Predicting Novel LncRNA-Disease Associations.
IEEE J. Biomed. Health Informatics, 2021
Multi-Label Fusion Collaborative Matrix Factorization for Predicting LncRNA-Disease Associations.
IEEE J. Biomed. Health Informatics, 2021
LWPCMF: Logistic Weighted Profile-Based Collaborative Matrix Factorization for Predicting MiRNA-Disease Associations.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
Dual Hyper-Graph Regularized Supervised NMF for Selecting Differentially Expressed Genes and Tumor Classification.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
DSTPCA: Double-Sparse Constrained Tensor Principal Component Analysis Method for Feature Selection.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
Kernel Risk-Sensitive Loss based Hyper-graph Regularized Robust Extreme Learning Machine and Its Semi-supervised Extension for Classification.
Knowl. Based Syst., 2021
Sparse robust graph-regularized non-negative matrix factorization based on correntropy.
J. Bioinform. Comput. Biol., 2021
DSCMF: prediction of LncRNA-disease associations based on dual sparse collaborative matrix factorization.
BMC Bioinform., 2021
MKL-LP: Predicting Disease-Associated Microbes with Multiple-Similarity Kernel Learning-Based Label Propagation.
Proceedings of the Bioinformatics Research and Applications - 17th International Symposium, 2021
Extreme Learning Machine Based on Double Kernel Risk-Sensitive Loss for Cancer Samples Classification.
Proceedings of the Intelligent Computing Theories and Application, 2021
Adaptive total-variation joint learning model for analyzing single cell RNA seq data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
Robust Tensor Method Based on Correntropy and Tensor Singular Value Decomposition for Cancer Genomics Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
2020
Integrative Hypergraph Regularization Principal Component Analysis for Sample Clustering and Co-Expression Genes Network Analysis on Multi-Omics Data.
IEEE J. Biomed. Health Informatics, 2020
Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification.
IEEE J. Biomed. Health Informatics, 2020
LncRNA-Disease Associations Prediction Using Bipartite Local Model With Nearest Profile-Based Association Inferring.
IEEE J. Biomed. Health Informatics, 2020
A multi-view classification and feature selection method via sparse low-rank regression analysis.
Int. J. Data Min. Bioinform., 2020
L<sub>2, 1</sub>-Extreme Learning Machine: An Efficient Robust Classifier for Tumor Classification.
Comput. Biol. Chem., 2020
MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations.
BMC Bioinform., 2020
Correntropy induced loss based sparse robust graph regularized extreme learning machine for cancer classification.
BMC Bioinform., 2020
Robust Graph Regularized Extreme Learning Machine Auto Encoder and Its Application to Single-Cell Samples Classification.
Proceedings of the Intelligent Computing Theories and Application, 2020
Locally Manifold Non-negative Matrix Factorization Based on Centroid for scRNA-seq Data Analysis.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
2019
The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method.
BMC Bioinform., December, 2019
Supervised Discriminative Sparse PCA for Com-Characteristic Gene Selection and Tumor Classification on Multiview Biological Data.
IEEE Trans. Neural Networks Learn. Syst., 2019
Differentially Expressed Genes Extracted by the Tensor Robust Principal Component Analysis (TRPCA) Method.
Complex., 2019
Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection.
Complex., 2019
Network analysis based on low-rank method for mining information on integrated data of multi-cancers.
Comput. Biol. Chem., 2019
NPCMF: Nearest Profile-based Collaborative Matrix Factorization method for predicting miRNA-disease associations.
BMC Bioinform., 2019
RCMF: a robust collaborative matrix factorization method to predict miRNA-disease associations.
BMC Bioinform., 2019
L2, 1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions.
BMC Bioinform., 2019
An Integrated Graph Regularized Non-Negative Matrix Factorization Model for Gene Co-Expression Network Analysis.
IEEE Access, 2019
DSNPCMF: Predicting MiRNA-Disease Associations with Collaborative Matrix Factorization Based on Double Sparse and Nearest Profile.
Proceedings of the Recent Advances in Data Science, 2019
Dual Sparse Collaborative Matrix Factorization Method Based on Gaussian Kernel Function for Predicting LncRNA-Disease Associations.
Proceedings of the Intelligent Computing Methodologies - 15th International Conference, 2019
2018
Regularized Non-Negative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Samples: A Survey.
IEEE ACM Trans. Comput. Biol. Bioinform., 2018
Proceedings of the Intelligent Computing Theories and Application, 2018
Hypergraph regularized NMF by L2, 1-norm for Clustering and Com-abnormal Expression Genes Selection.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018
2017
A joint-L<sub>2, 1</sub>-norm-constraint-based semi-supervised feature extraction for RNA-Seq data analysis.
Neurocomputing, 2017
A novel low-rank representation method for identifying differentially expressed genes.
Int. J. Data Min. Bioinform., 2017
Identifying drug-pathway association pairs based on L2, 1-integrative penalized matrix decomposition.
BMC Syst. Biol., 2017
Graph regularized robust non-negative matrix factorization for clustering and selecting differentially expressed genes.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017
Feature selection and clustering via robust graph-laplacian PCA based on capped L1-norm.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017
Low-rank representation regularized by L2, 1-norm for identifying differentially expressed genes.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017
2016
Characteristic Gene Selection Based on Robust Graph Regularized Non-Negative Matrix Factorization.
IEEE ACM Trans. Comput. Biol. Bioinform., 2016
A Class-Information-Based Sparse Component Analysis Method to Identify Differentially Expressed Genes on RNA-Seq Data.
IEEE ACM Trans. Comput. Biol. Bioinform., 2016
Differentially expressed genes selection via Laplacian regularized low-rank representation method.
Comput. Biol. Chem., 2016
Proceedings of the Intelligent Computing Theories and Application, 2016
Proceedings of the Intelligent Computing Theories and Application, 2016
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
A graph-Laplacian PCA based on L1/2-norm constraint for characteristic gene selection.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
2015
Application of Graph Regularized Non-negative Matrix Factorization in Characteristic Gene Selection.
Proceedings of the Intelligent Computing Theories and Methodologies, 2015
Graph Regularized Non-negative Matrix with L0-Constraints for Selecting Characteristic Genes.
Proceedings of the Intelligent Computing Theories and Methodologies, 2015
Proceedings of the Advanced Intelligent Computing Theories and Applications, 2015
Proceedings of the Intelligent Computing Theories and Methodologies, 2015