Ying-Lian Gao

102 papers Journal 66Unranked 36
YearRankTypeTitle / Venue / Authors
2026 J jnl
Deep association analysis framework with multi-modal attention fusion for brain imaging genetics.
Medical Image Anal.
Shuang-Qing Wang, Cui-Na Jiao, Ying-Lian Gao, Xinchun Cui, Yan-Li Wang, Jin-Xing Liu
2026 J jnl
Predicting microbe-disease associations based on multi-modal using reliable negative sample and cross attention network.
Eng. Appl. Artif. Intell.
Shuang Wang, Cui-Na Jiao, Xinchun Cui, Ying-Lian Gao, Jin-Xin Liu
2025 J jnl
SAMGCN: A spatially-augmented multi-view graph convolutional network for identifying spatial domains.
Eng. Appl. Artif. Intell.
Hao Liu, Yue Gao, Ying-Lian Gao, Cui-Na Jiao, Junliang Shang, Jin-Xing Liu
2025 J jnl
STDDAE: Identifying spatial domains in spatial transcriptomics by dual denoising autoencoder with attention mechanism.
Eng. Appl. Artif. Intell.
Yue Gao, Ying-Lian Gao, Cui-Na Jiao, Xu-Ran Dou, Feng Li, Jin-Xin Liu
2025 J jnl
SpaMGAN: Multi-view graph augmentation network for spatial domain identification in spatial transcriptomics.
Knowl. Based Syst.
Hao Liu, Yue Gao, Cui-Na Jiao, Chun-Hou Zheng, Ying-Lian Gao, Jin-Xing Liu, Yan-Li Wang
2025 J jnl
TEMCL: Prediction of Drug-Disease Associations Based on Transformer and Enhanced Multi-View Contrastive Learning.
IEEE J. Biomed. Health Informatics
Ming-Li Cui, Cui-Na Jiao, Ying-Lian Gao, Junliang Shang, Chun-Hou Zheng, Jin-Xing Liu
2025 J jnl
stDGAC: A novel identifying spatial domains method via graph attention contrastive network for spatial transcriptomics data.
Comput. Biol. Medicine
Jing Jing, Yue Gao, Ying-Lian Gao, Feng Li, Juan Wang, Jin-Xing Liu
2024 J jnl
A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection.
IEEE Trans. Neural Networks Learn. Syst.
Dai-Jun Zhang, Ying-Lian Gao, Jing-Xiu Zhao, Chun-Hou Zheng, Jin-Xing Liu
2024 J jnl
A review of recent advances in spatially resolved transcriptomics data analysis.
Neurocomputing
Yue Gao, Ying-Lian Gao, Jing Jing, Feng Li, Chun-Hou Zheng, Jin-Xing Liu
2024 J jnl
Diagnosis-Guided Deep Subspace Clustering Association Study for Pathogenetic Markers Identification of Alzheimer's Disease Based on Comparative Atlases.
IEEE J. Biomed. Health Informatics
Cui-Na Jiao, Junliang Shang, Feng Li, Xinchun Cui, Yan-Li Wang, Ying-Lian Gao, Jin-Xing Liu
2024 J jnl
Heterogeneous network and graph attention auto-encoder for LncRNA-disease association prediction.
CoRR
Jin-Xing Liu, Wen-Yu Xi, Ling-Yun Dai, Chun-Hou Zheng, Ying-Lian Gao
2024 — conf
Integrating Local and Global Information to Decipher Spatial Domains of Spatial Transcriptomics by Attention-based Graph Convolutional Network.
BIBM
Xu-Ran Dou, Yue Gao, Junliang Shang, Chun-Hou Zheng, Ying-Lian Gao, Jin-Xing Liu
2024 J jnl
KFDAE: CircRNA-Disease Associations Prediction Based on Kernel Fusion and Deep Auto-Encoder.
IEEE J. Biomed. Health Informatics
Wen-Yue Kang, Ying-Lian Gao, Ying Wang, Feng Li, Jin-Xing Liu
2024 J jnl
LncRNA-disease association prediction method based on heterogeneous information completion and convolutional neural network.
CoRR
Wen-Yu Xi, Juan Wang, Yu-lin Zhang, Jin-Xing Liu, Ying-Lian Gao
2024 J jnl
M
IEEE J. Biomed. Health Informatics
Shuang Wang, Jin-Xing Liu, Feng Li, Juan Wang, Ying-Lian Gao
2024 J jnl
Multi-Kernel Graph Attention Deep Autoencoder for MiRNA-Disease Association Prediction.
IEEE J. Biomed. Health Informatics
Cui-Na Jiao, Feng Zhou, Bao-Min Liu, Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao
2024 J jnl
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.
Cui-Na Jiao, Ying-Lian Gao, Dao-Hui Ge, Junliang Shang, Jin-Xing Liu
2024 J jnl
SLGCN: Structure-enhanced line graph convolutional network for predicting drug-disease associations.
Knowl. Based Syst.
Bao-Min Liu, Ying-Lian Gao, Feng Li, Chun-Hou Zheng, Jin-Xing Liu
2024 — conf
stMCFN: A Multi-view Contrastive Fusion Method for Spatial Domain Identification in Spatial Transcriptomics.
ICIC (LNBI 1)
Jing Jing, Ying-Lian Gao, Yue Gao, Dao-Hui Ge, Chun-Hou Zheng, Jin-Xing Liu
2023 J jnl
A Graph Representation Approach Based on Light Gradient Boosting Machine for Predicting Drug-Disease Associations.
J. Comput. Biol.
Ying Wang, Jin-Xing Liu, Juan Wang, Junliang Shang, Ying-Lian Gao
2023 J jnl
BRWMC: Predicting lncRNA-disease associations based on bi-random walk and matrix completion on disease and lncRNA networks.
Comput. Biol. Chem.
Guozheng Zhang, Ying-Lian Gao
2023 J jnl
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
Ying-Lian Gao, Qian Qiao, Juan Wang, Shasha Yuan, Jin-Xing Liu
2023 — conf
GRPGAT: Predicting CircRNA-disease Associations Based on Graph Random Propagation Network and Graph Attention Network.
BIBM
Wen-Yue Kang, Chun-Hou Zheng, Ying-Lian Gao, Juan Wang, Junliang Shang, Jin-Xing Liu
2023 J jnl
Identification of Disease-Associated MicroRNAs Via Locality-Constrained Linear Coding-Based Ensemble Learning.
J. Comput. Biol.
Yi Shen, Ying-Lian Gao, Juan Wang, Boxin Guan, Jin-Xing Liu
2023 — conf
Identify Complex Higher-Order Associations Between Alzheimer's Disease Genes and Imaging Markers Through Improved Adaptive Sparse Multi-view Canonical Correlation Analysis.
ICIC (3)
Yi-Ming Wang, Xiang-Zhen Kong, Boxin Guan, Chun-Hou Zheng, Ying-Lian Gao
2023 — conf
LANCMDA: Predicting MiRNA-Disease Associations via LightGBM with Attributed Network Construction.
ICIC (3)
Xu-Ran Dou, Wen-Yu Xi, Tian-Ru Wu, Cui-Na Jiao, Jin-Xing Liu, Ying-Lian Gao
2023 J jnl
LDCMFC: Predicting Long Non-Coding RNA and Disease Association Using Collaborative Matrix Factorization Based on Correntropy.
IEEE ACM Trans. Comput. Biol. Bioinform.
Wen-Yu Xi, Feng Zhou, Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng
2023 — conf
MKGSAGE: A Computational Framework via Multiple Kernel Fusion on GraphSAGE for Inferring Potential Disease-Related Microbes.
BIBM
Shuang Wang, Jin-Xing Liu, Bao-Min Liu, Ling-Yun Dai, Feng Li, Ying-Lian Gao
2023 J jnl
MSF-LRR: Multi-Similarity Information Fusion Through Low-Rank Representation to Predict Disease-Associated Microbes.
IEEE ACM Trans. Comput. Biol. Bioinform.
Jin-Xing Liu, Meng-Meng Yin, Ying-Lian Gao, Junliang Shang, Chun-Hou Zheng
2023 J jnl
MSGCA: Drug-Disease Associations Prediction Based on Multi-Similarities Graph Convolutional Autoencoder.
IEEE J. Biomed. Health Informatics
Ying Wang, Ying-Lian Gao, Juan Wang, Feng Li, Jin-Xing Liu
2023 J jnl
NTBiRW: A Novel Neighbor Model Based on Two-Tier Bi-Random Walk for Predicting Potential Disease-Related Microbes.
IEEE J. Biomed. Health Informatics
Meng-Meng Yin, Ying-Lian Gao, Chun-Hou Zheng, Jin-Xing Liu
2023 J jnl
Non-Negative Low-Rank Representation With Similarity Correction for Cell Type Identification in scRNA-Seq Data.
IEEE ACM Trans. Comput. Biol. Bioinform.
Jin-Xing Liu, Dai-Jun Zhang, Jing-Xiu Zhao, Chun-Hou Zheng, Ying-Lian Gao
2023 — conf
Spatial Domain Identification Based on Graph Attention Denoising Auto-encoder.
ICIC (3)
Yue Gao, Dai-Jun Zhang, Cui-Na Jiao, Ying-Lian Gao, Jin-Xing Liu
2022 — conf
A Locality-Constrained Linear Coding-Based Ensemble Learning Framework for Predicting Potentially Disease-Associated MiRNAs.
ISBRA
Yi Shen, Ying-Lian Gao, Shu-Zhen Li, Boxin Guan, Jin-Xing Liu
2022 J jnl
A new framework for drug-disease association prediction combing light-gated message passing neural network and gated fusion mechanism.
Briefings Bioinform.
Bao-Min Liu, Ying-Lian Gao, Dai-Jun Zhang, Feng Zhou, Juan Wang, Chun-Hou Zheng, Jin-Xing Liu
2022 — conf
An integrated Extreme learning machine based on kernel risk-sensitive loss of q-Gaussian and voting mechanism for sample classification.
BIBM
Zhi-yuan Li, Ying-Lian Gao, Zhen-Xin Niu, Shasha Yuan, Chun-Hou Zheng, Jin-Xing Liu
2022 — conf
HSAELDA: Predicting lncRNA-disease associations based on heterogeneous networks and Stacked Autoencoder.
BIBM
Wen-Yu Xi, Qianqian Ren, Jin-Xing Liu, Ying-Lian Gao
2022 J jnl
Kernel risk-sensitive mean p-power error based robust extreme learning machine for classification.
Int. J. Mach. Learn. Cybern.
Liang-Rui Ren, Ying-Lian Gao, Junliang Shang, Jin-Xing Liu
2022 — conf
MLMVFE: A Machine Learning Approach Based on Muli-view Features Extraction for Drug-Disease Associations Prediction.
ISBRA
Ying Wang, Ying-Lian Gao, Juan Wang, Junliang Shang, Jin-Xing Liu
2022 J jnl
Multi-similarity fusion-based label propagation for predicting microbes potentially associated with diseases.
Future Gener. Comput. Syst.
Meng-Meng Yin, Ying-Lian Gao, Junliang Shang, Chun-Hou Zheng, Jin-Xing Liu
2022 J jnl
NCPLP: A Novel Approach for Predicting Microbe-Associated Diseases With Network Consistency Projection and Label Propagation.
IEEE Trans. Cybern.
Meng-Meng Yin, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Chun-Hou Zheng
2022 — conf
Predicting LncRNA-Disease Associations Based on LncRNA-MiRNA-Disease Multilayer Association Network and Bipartite Network Recommendation.
BIBM
Guozheng Zhang, Shu-Zhen Li, Xu-Ran Dou, Junliang Shang, Qianqian Ren, Ying-Lian Gao
2022 J jnl
Robust Principal Component Analysis Based On Hypergraph Regularization for Sample Clustering and Co-Characteristic Gene Selection.
IEEE ACM Trans. Comput. Biol. Bioinform.
Ying-Lian Gao, Ming-Juan Wu, Jin-Xing Liu, Chun-Hou Zheng, Juan Wang
2022 J jnl
Single-Cell RNA Sequencing Data Clustering by Low-Rank Subspace Ensemble Framework.
IEEE ACM Trans. Comput. Biol. Bioinform.
Chuan-Yuan Wang, Ying-Lian Gao, Jin-Xing Liu, Xiang-Zhen Kong, Chun-Hou Zheng
2022 J jnl
Tensor decomposition based on the potential low-rank and p-shrinkage generalized threshold algorithm for analyzing cancer multiomics data.
J. Bioinform. Comput. Biol.
Hang-Jin Yang, Yuxia Lei, Juan Wang, Xiang-Zhen Kong, Jin-Xing Liu, Ying-Lian Gao
2022 J jnl
Unsupervised Cluster Analysis and Gene Marker Extraction of scRNA-seq Data Based On Non-Negative Matrix Factorization.
IEEE J. Biomed. Health Informatics
Chuan-Yuan Wang, Ying-Lian Gao, Xiang-Zhen Kong, Jin-Xing Liu, Chun-Hou Zheng
2021 — conf
Adaptive total-variation joint learning model for analyzing single cell RNA seq data.
BIBM
Dai-Jun Zhang, Jing-Xiu Zhao, Jin-Xing Liu, Ying-Lian Gao
2021 J jnl
DSCMF: prediction of LncRNA-disease associations based on dual sparse collaborative matrix factorization.
BMC Bioinform.
Jin-Xing Liu, Ming-Ming Gao, Zhen Cui, Ying-Lian Gao, Feng Li
2021 J jnl
DSTPCA: Double-Sparse Constrained Tensor Principal Component Analysis Method for Feature Selection.
IEEE ACM Trans. Comput. Biol. Bioinform.
Yue Hu, Jin-Xing Liu, Ying-Lian Gao, Junliang Shang
2021 J jnl
Dual Hyper-Graph Regularized Supervised NMF for Selecting Differentially Expressed Genes and Tumor Classification.
IEEE ACM Trans. Comput. Biol. Bioinform.
Chuan-Yuan Wang, Na Yu, Ming-Juan Wu, Ying-Lian Gao, Jin-Xing Liu, Juan Wang
2021 — conf
Extreme Learning Machine Based on Double Kernel Risk-Sensitive Loss for Cancer Samples Classification.
ICIC (2)
Zhen-Xin Niu, Liang-Rui Ren, Rong Zhu, Xiang-Zhen Kong, Ying-Lian Gao, Jin-Xing Liu
2021 J jnl
Kernel Risk-Sensitive Loss based Hyper-graph Regularized Robust Extreme Learning Machine and Its Semi-supervised Extension for Classification.
Knowl. Based Syst.
Liang-Rui Ren, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Chun-Hou Zheng
2021 J jnl
LWPCMF: Logistic Weighted Profile-Based Collaborative Matrix Factorization for Predicting MiRNA-Disease Associations.
IEEE ACM Trans. Comput. Biol. Bioinform.
Meng-Meng Yin, Zhen Cui, Ming-Ming Gao, Jin-Xing Liu, Ying-Lian Gao
2021 — conf
MKL-LP: Predicting Disease-Associated Microbes with Multiple-Similarity Kernel Learning-Based Label Propagation.
ISBRA
Ying-Lian Gao, Meng-Meng Yin, Jin-Xing Liu, Junliang Shang, Chun-Hou Zheng
2021 J jnl
Multi-Label Fusion Collaborative Matrix Factorization for Predicting LncRNA-Disease Associations.
IEEE J. Biomed. Health Informatics
Ming-Ming Gao, Zhen Cui, Ying-Lian Gao, Juan Wang, Jin-Xing Liu
2021 — conf
Robust Tensor Method Based on Correntropy and Tensor Singular Value Decomposition for Cancer Genomics Data.
BIBM
Qian Qiao, Ying-Lian Gao, Shasha Yuan, Jin-Xing Liu
2021 — conf
Sparse Hyper-graph Non-negative Matrix Factorization by Maximizing Correntropy.
BIBM
Cui-Na Jiao, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Chun-Hou Zheng, Xianzi Yu
2021 J jnl
Sparse robust graph-regularized non-negative matrix factorization based on correntropy.
J. Bioinform. Comput. Biol.
Chuan-Yuan Wang, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Junliang Shang
2021 J jnl
WGRCMF: A Weighted Graph Regularized Collaborative Matrix Factorization Method for Predicting Novel LncRNA-Disease Associations.
IEEE J. Biomed. Health Informatics
Jin-Xing Liu, Zhen Cui, Ying-Lian Gao, Xiang-Zhen Kong
2020 J jnl
A multi-view classification and feature selection method via sparse low-rank regression analysis.
Int. J. Data Min. Bioinform.
Yao Lu, Ying-Lian Gao, Pei-Yong Li, Jin-Xing Liu
2020 J jnl
Correntropy induced loss based sparse robust graph regularized extreme learning machine for cancer classification.
BMC Bioinform.
Liang-Rui Ren, Ying-Lian Gao, Jin-Xing Liu, Junliang Shang, Chun-Hou Zheng
2020 J jnl
Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification.
IEEE J. Biomed. Health Informatics
Cui-Na Jiao, Ying-Lian Gao, Na Yu, Jin-Xing Liu, Lianyong Qi
2020 J jnl
Integrative Hypergraph Regularization Principal Component Analysis for Sample Clustering and Co-Expression Genes Network Analysis on Multi-Omics Data.
IEEE J. Biomed. Health Informatics
Ming-Juan Wu, Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng, Juan Wang
2020 J jnl
L
Comput. Biol. Chem.
Liang-Rui Ren, Ying-Lian Gao, Jin-Xing Liu, Rong Zhu, Xiang-Zhen Kong
2020 J jnl
LncRNA-Disease Associations Prediction Using Bipartite Local Model With Nearest Profile-Based Association Inferring.
IEEE J. Biomed. Health Informatics
Zhen Cui, Jin-Xing Liu, Ying-Lian Gao, Rong Zhu, Shasha Yuan
2020 — conf
Locally Manifold Non-negative Matrix Factorization Based on Centroid for scRNA-seq Data Analysis.
BIBM
Chuan-Yuan Wang, Ying-Lian Gao, Cui-Na Jiao, Jin-Xing Liu, Chunhou Zheng, Xiang-Zhen Kong
2020 J jnl
MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations.
BMC Bioinform.
Tian-Ru Wu, Meng-Meng Yin, Cui-Na Jiao, Ying-Lian Gao, Xiang-Zhen Kong, Jin-Xing Liu
2020 — conf
Robust Graph Regularized Extreme Learning Machine Auto Encoder and Its Application to Single-Cell Samples Classification.
ICIC (2)
Liang-Rui Ren, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Chun-Hou Zheng
2019 J jnl
An Integrated Graph Regularized Non-Negative Matrix Factorization Model for Gene Co-Expression Network Analysis.
IEEE Access
Ying-Lian Gao, Mi-Xiao Hou, Jin-Xing Liu, Xiang-Zhen Kong
2019 — conf
DSNPCMF: Predicting MiRNA-Disease Associations with Collaborative Matrix Factorization Based on Double Sparse and Nearest Profile.
IDMB
Meng-Meng Yin, Zhen Cui, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong
2019 J jnl
Differentially Expressed Genes Extracted by the Tensor Robust Principal Component Analysis (TRPCA) Method.
Complex.
Yue Hu, Jin-Xing Liu, Ying-Lian Gao, Shengjun Li, Juan Wang
2019 — conf
Dual Sparse Collaborative Matrix Factorization Method Based on Gaussian Kernel Function for Predicting LncRNA-Disease Associations.
ICIC (3)
Ming-Ming Gao, Zhen Cui, Ying-Lian Gao, Feng Li, Jin-Xing Liu
2019 J jnl
Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection.
Complex.
Yong-Jing Hao, Ying-Lian Gao, Mi-Xiao Hou, Ling-Yun Dai, Jin-Xing Liu
2019 J jnl
L2, 1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions.
BMC Bioinform.
Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Shasha Yuan
2019 J jnl
NPCMF: Nearest Profile-based Collaborative Matrix Factorization method for predicting miRNA-disease associations.
BMC Bioinform.
Ying-Lian Gao, Zhen Cui, Jin-Xing Liu, Juan Wang, Chun-Hou Zheng
2019 J jnl
Network analysis based on low-rank method for mining information on integrated data of multi-cancers.
Comput. Biol. Chem.
Mi-Xiao Hou, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Xiangzhen Kong, Junliang Shang
2019 J jnl
RCMF: a robust collaborative matrix factorization method to predict miRNA-disease associations.
BMC Bioinform.
Zhen Cui, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Juan Wang
2019 J jnl
Supervised Discriminative Sparse PCA for Com-Characteristic Gene Selection and Tumor Classification on Multiview Biological Data.
CoRR
Chun-Mei Feng, Yong Xu, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng
2019 J jnl
Supervised Discriminative Sparse PCA for Com-Characteristic Gene Selection and Tumor Classification on Multiview Biological Data.
IEEE Trans. Neural Networks Learn. Syst.
Chun-Mei Feng, Yong Xu, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng
2019 J jnl
The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method.
BMC Bioinform.
Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang, Ling-Yun Dai
2018 — conf
Hypergraph regularized NMF by L2, 1-norm for Clustering and Com-abnormal Expression Genes Selection.
BIBM
Na Yu, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang
2018 — conf
Performance Analysis of Non-negative Matrix Factorization Methods on TCGA Data.
ICIC (2)
Mi-Xiao Hou, Jin-Xing Liu, Junliang Shang, Ying-Lian Gao, Xiangzhen Kong, Ling-Yun Dai
2018 J jnl
Regularized Non-Negative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Samples: A Survey.
IEEE ACM Trans. Comput. Biol. Bioinform.
Jin-Xing Liu, Dong Wang, Ying-Lian Gao, Chun-Hou Zheng, Yong Xu, Jiguo Yu
2017 J jnl
A joint-L
Neurocomputing
Jin-Xing Liu, Dong Wang, Ying-Lian Gao, Chun-Hou Zheng, Junliang Shang, Feng Liu, Yong Xu
2017 J jnl
A novel low-rank representation method for identifying differentially expressed genes.
Int. J. Data Min. Bioinform.
Xiu-Xiu Xu, Ying-Lian Gao, Jin-Xing Liu, Yaxuan Wang, Ling-Yun Dai, Xiangzhen Kong, Shasha Yuan
2017 — conf
Feature selection and clustering via robust graph-laplacian PCA based on capped L1-norm.
BIBM
Ming-Juan Wu, Jin-Xing Liu, Ying-Lian Gao, Xiangzhen Kong, Chun-Mei Feng
2017 — conf
Graph regularized robust non-negative matrix factorization for clustering and selecting differentially expressed genes.
BIBM
Na Yu, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Juan Wang, Ming-Juan Wu
2017 J jnl
Identifying drug-pathway association pairs based on L2, 1-integrative penalized matrix decomposition.
BMC Syst. Biol.
Jin-Xing Liu, Dong-Qin Wang, Chun-Hou Zheng, Ying-Lian Gao, Sha-Sha Wu, Junliang Shang
2017 — conf
Low-rank representation regularized by L2, 1-norm for identifying differentially expressed genes.
BIBM
Yaxuan Wang, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Ling-Yun Dai
2016 J jnl
A Class-Information-Based Sparse Component Analysis Method to Identify Differentially Expressed Genes on RNA-Seq Data.
IEEE ACM Trans. Comput. Biol. Bioinform.
Jin-Xing Liu, Yong Xu, Ying-Lian Gao, Chun-Hou Zheng, Dong Wang, Qi Zhu
2016 — conf
A Simple Review of Sparse Principal Components Analysis.
ICIC (2)
Chun-Mei Feng, Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng, Shengjun Li, Dong Wang
2016 — conf
A graph-Laplacian PCA based on L1/2-norm constraint for characteristic gene selection.
BIBM
Chun-Mei Feng, Jin-Xing Liu, Ying-Lian Gao, Juan Wang, Dong-Qin Wang, Yong Du
2016 J jnl
Characteristic Gene Selection Based on Robust Graph Regularized Non-Negative Matrix Factorization.
IEEE ACM Trans. Comput. Biol. Bioinform.
Dong Wang, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Yong Xu
2016 — conf
Characteristic gene selection via L2, 1-norm Sparse Principal Component Analysis.
BIBM
Yao Lu, Ying-Lian Gao, Jin-Xing Liu, Chang-Gang Wen, Yaxuan Wang, Jiguo Yu
2016 — conf
Comparison of Non-negative Matrix Factorization Methods for Clustering Genomic Data.
ICIC (2)
Mi-Xiao Hou, Ying-Lian Gao, Jin-Xing Liu, Junliang Shang, Chun-Hou Zheng
2016 J jnl
Differentially expressed genes selection via Laplacian regularized low-rank representation method.
Comput. Biol. Chem.
Yaxuan Wang, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Junliang Shang
2016 — conf
Differentially expressed genes selection via Truncated Nuclear Norm Regularization.
BIBM
Yaxuan Wang, Jin-Xing Liu, Ying-Lian Gao, Xiangzhen Kong, Chun-Hou Zheng, Yong Du
2016 — conf
L21-iPaD: An efficient method for drug-pathway association pairs inference.
BIBM
Dong-Qin Wang, Chun-Hou Zheng, Ying-Lian Gao, Jin-Xing Liu, Sha-Sha Wu, Junliang Shang
2015 — conf
A Two-Stage Sparse Selection Method for Extracting Characteristic Genes.
ICIC (2)
Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng, Shengjun Li, Yuxia Lei
2015 — conf
Application of Graph Regularized Non-negative Matrix Factorization in Characteristic Gene Selection.
ICIC (2)
Dong Wang, Ying-Lian Gao, Jin-Xing Liu, Jiguo Yu, Chang-Gang Wen
2015 — conf
Graph Regularized Non-negative Matrix with L0-Constraints for Selecting Characteristic Genes.
ICIC (2)
Chun-Xia Ma, Ying-Lian Gao, Dong Wang, Jian Liu, Jin-Xing Liu
2015 — conf
Semi-supervised Feature Extraction for RNA-Seq Data Analysis.
ICIC (3)
Jin-Xing Liu, Yong Xu, Ying-Lian Gao, Dong Wang, Chun-Hou Zheng, Junliang Shang