Ying-Lian Gao

发表

Application of a Deep Matrix Factorization Model on Integrated Gene Expression Data

Mi-Xiao Hou, Jin-Xing Liu, Yong-Jing Hao, 2020, Current Bioinformatics.

Differential Expression Analysis on RNA-Seq Count Data Based on Penalized Matrix Decomposition

J. You, C. Zheng, Jin-Xing Liu, 2014, IEEE Transactions on NanoBioscience.

Robust Principal Component Analysis Regularized by Truncated Nuclear Norm for Identifying Differentially Expressed Genes

Jin-Xing Liu, Ying-Lian Gao, Xiangzhen Kong, 2017, IEEE Transactions on NanoBioscience.

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

Jin-Xing Liu, Ying-Lian Gao, Xiangzhen Kong, 2015, PloS one.

A Class-Information-Based Penalized Matrix Decomposition for Identifying Plants Core Genes Responding to Abiotic Stresses

Jian-Xun Mi, Jin-Xing Liu, Ying-Lian Gao, 2014, PloS one.

Coexpression Module Discovery Based on Gene Expression Data

Jin-Xing Liu, Ying-Lian Gao, Dong Wang, 2016 .

DSNPCMF: Predicting MiRNA-Disease Associations with Collaborative Matrix Factorization Based on Double Sparse and Nearest Profile

Jin-Xing Liu, Ying-Lian Gao, Xiangzhen Kong, 2019, IDMB.

A Class-information-based SNMF method for selecting characteristic genes

C. Zheng, Jin-Xing Liu, Ying-Lian Gao, 2014, 2014 8th International Conference on Systems Biology (ISB).

MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations

Jin-Xing Liu, Ying-Lian Gao, Xiangzhen Kong, 2020, BMC Bioinformatics.

C. Zheng, Jin-Xing Liu, Ying-Lian Gao, 2022, Future Gener. Comput. Syst..

BMPMDA: Prediction of MiRNA-Disease Associations Using a Space Projection Model Based on Block Matrix

C. Zheng, Jin-Xing Liu, Ying-Lian Gao, 2022, Interdisciplinary Sciences: Computational Life Sciences.

Adaptive Total-Variation Regularized Low-Rank Representation for Analyzing Single-Cell RNA-seq Data

Jin-Xing Liu, Ying-Lian Gao, Juan Wang, 2021, Interdisciplinary Sciences: Computational Life Sciences.

Identifying drug-pathway association pairs based on L2,1-integrative penalized matrix decomposition

Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao, 2017, BMC Systems Biology.

Identifying drug-pathway association pairs based on L1L2,1-integrative penalized matrix decomposition

Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao, 2017, Oncotarget.

L21-iPaD: An efficient method for drug-pathway association pairs inference

Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao, 2016, 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Block-Constraint Robust Principal Component Analysis and its Application to Integrated Analysis of TCGA Data

Jiguo Yu, Yong Xu, Chun-Hou Zheng, 2016, IEEE Transactions on NanoBioscience.

Regularized Non-Negative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Samples: A Survey

Jiguo Yu, Yong Xu, Chun-Hou Zheng, 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Differentially expressed genes selection via Laplacian regularized low-rank representation method

Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao, 2016, Comput. Biol. Chem..

LncRNA-Disease Associations Prediction Using Bipartite Local Model With Nearest Profile-Based Association Inferring

Zhen Cui, Jin-Xing Liu, Ying-Lian Gao, 2020, IEEE Journal of Biomedical and Health Informatics.

Single-Cell RNA Sequencing Data Clustering by Low-Rank Subspace Ensemble Framework

Chun-Hou Zheng, Ying-Lian Gao, Jin-Xing Liu, 2020, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

DSCMF: prediction of LncRNA-disease associations based on dual sparse collaborative matrix factorization

Jin-Xing Liu, Ying-Lian Gao, Zhen Cui, 2021, BMC Bioinformatics.

Locally Manifold Non-negative Matrix Factorization Based on Centroid for scRNA-seq Data Analysis

Ying-Lian Gao, Xiang-Zhen Kong, Cui-Na Jiao, 2020, 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Characteristic Gene Selection Based on Robust Graph Regularized Non-Negative Matrix Factorization

Yong Xu, Chun-Hou Zheng, Jin-Xing Liu, 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

RCMF: a robust collaborative matrix factorization method to predict miRNA-disease associations

Juan Wang, Chun-Hou Zheng, Jin-Xing Liu, 2019, BMC Bioinformatics.

NPCMF: Nearest Profile-based Collaborative Matrix Factorization method for predicting miRNA-disease associations

Chun-Hou Zheng, Juan Wang, Jin-Xing Liu, 2019, BMC Bioinformatics.

Dual-network sparse graph regularized matrix factorization for predicting miRNA-disease associations.

Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao, 2019, Molecular omics.

LWPCMF: Logistic Weighted Profile-Based Collaborative Matrix Factorization for Predicting MiRNA-Disease Associations

Zhen Cui, Jin-Xing Liu, Ying-Lian Gao, 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

A joint-L2, 1-norm-constraint-based semi-supervised feature extraction for RNA-Seq data analysis

Feng Liu, Chun-Hou Zheng, Jin-Xing Liu, 2017, Neurocomputing.

MSF-LRR: Multi-Similarity Information Fusion Through Low-Rank Representation to Predict Disease-Associated Microbes

C. Zheng, Jin-Xing Liu, Ying-Lian Gao, 2022, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Network analysis based on low-rank method for mining information on integrated data of multi-cancers

Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, 2019, Comput. Biol. Chem..

CNLLRR: A Novel Low-Rank Representation Method for Single-cell RNA-seq Data Analysis

Hongmin Cai, Chun-Hou Zheng, Ying-Lian Gao, 2019, bioRxiv.

DSTPCA: Double-Sparse Constrained Tensor Principal Component Analysis Method for Feature Selection

Yue Hu, Jin-Xing Liu, Ying-Lian Gao, 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

L2,1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions

Jin-Xing Liu, Ying-Lian Gao, Lingyun Dai, 2019, BMC Bioinformatics.

Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification

Ying-Lian Gao, Cui-Na Jiao, Jin-Xing Liu, 2020, IEEE Journal of Biomedical and Health Informatics.

Characteristic gene selection via L2,1-norm Sparse Principal Component Analysis

Jiguo Yu, Jin-Xing Liu, Ying-Lian Gao, 2016, 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Multi-Label Fusion Collaborative Matrix Factorization for Predicting LncRNA-Disease Associations

Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, 2020, IEEE Journal of Biomedical and Health Informatics.

WGRCMF: A Weighted Graph Regularized Collaborative Matrix Factorization Method for Predicting Novel LncRNA-Disease Associations

Zhen Cui, Ying-Lian Gao, Xiang-Zhen Kong, 2020, IEEE Journal of Biomedical and Health Informatics.

BRWMC: Predicting lncRNA-disease associations based on bi-random walk and matrix completion on disease and lncRNA networks

Ying-Lian Gao, Guo-Zheng Zhang, 2023, Comput. Biol. Chem..

Integrative Hypergraph Regularization Principal Component Analysis for Sample Clustering and Co-Expression Genes Network Analysis on Multi-Omics Data

Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao, 2020, IEEE Journal of Biomedical and Health Informatics.

Joint L1/2-Norm Constraint and Graph-Laplacian PCA Method for Feature Extraction

Jin-Xing Liu, Ying-Lian Gao, Juan Wang, 2017, BioMed research international.

Application of Graph Regularized Non-negative Matrix Factorization in Characteristic Gene Selection

Jiguo Yu, Jin-Xing Liu, Ying-Lian Gao, 2015, ICIC.

Kernel Risk-Sensitive Loss based Hyper-graph Regularized Robust Extreme Learning Machine and Its Semi-supervised Extension for Classification

Jin-Xing Liu, Ying-Lian Gao, Liang-Rui Ren, 2021, Knowl. Based Syst..

Kernel risk-sensitive mean p-power error based robust extreme learning machine for classification

Jin-Xing Liu, Ying-Lian Gao, Junliang Shang, 2021, Int. J. Mach. Learn. Cybern..

Kernel risk-sensitive mean p-power error based robust extreme learning machine for classification

Ying-Lian Gao, J. Shang, Jinxing Liu, 2021, International Journal of Machine Learning and Cybernetics.

Correntropy induced loss based sparse robust graph regularized extreme learning machine for cancer classification

Chun-Hou Zheng, Liang-Rui Ren, Ying-Lian Gao, 2020, BMC Bioinform..

Differentially Expressed Genes Extracted by the Tensor Robust Principal Component Analysis (TRPCA) Method

Yue Hu, Jin-Xing Liu, Ying-Lian Gao, 2019, Complex..

A Simple Review of Sparse Principal Components Analysis

Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao, 2016, ICIC.

A new method for mining information of co-expression network based on multi-cancers integrated data

Jin-Xing Liu, Ying-Lian Gao, Junliang Shang, 2019, BMC Medical Genomics.

Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection

Jin-Xing Liu, Ying-Lian Gao, Yong-Jing Hao, 2019, Complex..

Co-differential Gene Selection and Clustering Based on Graph Regularized Multi-View NMF in Cancer Genomic Data

Rong Zhu, Jin-Xing Liu, Ying-Lian Gao, 2018, Genes.

Supervised Discriminative Sparse PCA for Com-Characteristic Gene Selection and Tumor Classification on Multiview Biological Data

Yong Xu, Chun-Hou Zheng, Jin-Xing Liu, 2019, IEEE Transactions on Neural Networks and Learning Systems.

NCPLP: A Novel Approach for Predicting Microbe-Associated Diseases With Network Consistency Projection and Label Propagation

Chun-Hou Zheng, Ying-Lian Gao, Xiang-Zhen Kong, 2020, IEEE Transactions on Cybernetics.

NPCMF: Nearest Profile-based Collaborative Matrix Factorization method for predicting miRNA-disease associations

C. Zheng, Jin-Xing Liu, Ying-Lian Gao, 2019, BMC Bioinformatics.

A New Model of Identifying Differentially Expressed Genes via Weighted Network Analysis Based on Dimensionality Reduction Method

Jin-Xing Liu, Ying-Lian Gao, Jin-Xing Liu, 2019 .

PCA Based on Graph Laplacian Regularization and P-Norm for Gene Selection and Clustering

Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao, 2017, IEEE Transactions on NanoBioscience.

An Integrated Graph Regularized Non-Negative Matrix Factorization Model for Gene Co-Expression Network Analysis

Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, 2019, IEEE Access.

Hypergraph regularized NMF by L2,1-norm for Clustering and Com-abnormal Expression Genes Selection

Jin-Xing Liu, Ying-Lian Gao, Na Yu, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Regularized Non-Negative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Samples: A Survey

C. Zheng, Jin-Xing Liu, Ying-Lian Gao, 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Graph regularized robust non-negative matrix factorization for clustering and selecting differentially expressed genes

Juan Wang, Chun-Hou Zheng, Jin-Xing Liu, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Robust hypergraph regularized non-negative matrix factorization for sample clustering and feature selection in multi-view gene expression data

Juan Wang, Jin-Xing Liu, Ying-Lian Gao, 2019, Human Genomics.

Comparison of Non-negative Matrix Factorization Methods for Clustering Genomic Data

Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao, 2016, ICIC.

L2, 1-Extreme Learning Machine: An Efficient Robust Classifier for Tumor Classification

Rong Zhu, Liang-Rui Ren, Ying-Lian Gao, 2020, Comput. Biol. Chem..

LDCMFC: Predicting Long Non-Coding RNA and Disease Association Using Collaborative Matrix Factorization Based on Correntropy

C. Zheng, Jin-Xing Liu, Ying-Lian Gao, 2022, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

An NMF-L2,1-Norm Constraint Method for Characteristic Gene Selection

Jiguo Yu, Chun-Hou Zheng, Jin-Xing Liu, 2016, PloS one.

MSGCA: Drug-Disease Associations Prediction Based on Multi-Similarities Graph Convolutional Autoencoder

Y. Wang, Jin-Xing Liu, Ying-Lian Gao, 2023, IEEE journal of biomedical and health informatics.

A new framework for drug-disease association prediction combing light-gated message passing neural network and gated fusion mechanism

C. Zheng, Jin-Xing Liu, Ying-Lian Gao, 2022, Briefings Bioinform..

Unsupervised Cluster Analysis and Gene Marker Extraction of scRNA-seq Data Based On Non-Negative Matrix Factorization

Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao, 2021, IEEE Journal of Biomedical and Health Informatics.

A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection

C. Zheng, Jin-Xing Liu, Ying-Lian Gao, 2022, IEEE Transactions on Neural Networks and Learning Systems.

Multi-Kernel Graph Attention Deep Autoencoder for MiRNA-Disease Association Prediction

Jin-Xing Liu, Ying-Lian Gao, Cui-Na Jiao, 2023, IEEE Journal of Biomedical and Health Informatics.

Identification of Disease-Associated MicroRNAs Via Locality-Constrained Linear Coding-Based Ensemble Learning

Jin-Xing Liu, Ying-Lian Gao, Juan Wang, 2023, J. Comput. Biol..

NTBiRW: A Novel Neighbor Model Based on Two-Tier Bi-Random Walk for Predicting Potential Disease-Related Microbes

C. Zheng, Jin-Xing Liu, Ying-Lian Gao, 2023, IEEE Journal of Biomedical and Health Informatics.

MKL-LP: Predicting Disease-Associated Microbes with Multiple-Similarity Kernel Learning-Based Label Propagation

Jin-Xing Liu, Ying-Lian Gao, Meng-Meng Yin, 2021, ISBRA.

Non-Negative Low-Rank Representation With Similarity Correction for Cell Type Identification in scRNA-Seq Data

Ying-Lian Gao, Dai-Jun Zhang, Jing-Xiu Zhao, 2023, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Predicting LncRNA-Disease Associations Based on LncRNA-MiRNA-Disease Multilayer Association Network and Bipartite Network Recommendation

Ying-Lian Gao, J. Shang, Guo-Zheng Zhang, 2022, 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

SLGCN: Structure-enhanced line graph convolutional network for predicting drug-disease associations

Jin-Xing Liu, Ying-Lian Gao, Bao-Min Liu, 2024, Knowl. Based Syst..

A review of recent advances in spatially resolved transcriptomics data analysis

Jin-Xing Liu, Ying-Lian Gao, Chunhou Zheng, 2024, Neurocomputing.

Robust Graph Regularized Extreme Learning Machine Auto Encoder and Its Application to Single-Cell Samples Classification

Chun-Hou Zheng, Jin-Xing Liu, Liang-Rui Ren, 2020, ICIC.