Jin-Xing Liu

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 170

Top Venues

BIBM

IEEE ACM Trans. Comput. Biol. Bioinform.

IEEE J. Biomed. Health Informatics

BMC Bioinform.

Publications

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)
Xinchun Cui, Youshi Zhou, Chao Zhao, Jianlong Li, Xiangwei Zheng, Xiuli Li, Shixiao Shan, Jin-Xing Liu, Xiaoli Liu
A Multiscale Hybrid Attention Networks Based on Multiview Images for the Diagnosis of Parkinson's Disease. IEEE Trans. Instrum. Meas. 73 (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)
Zhen-Chang Wang, Jin-Xing Liu, Junliang Shang, Ling-Yun Dai, Chun-Hou Zheng, Juan Wang
ARGLRR: A Sparse Low-Rank Representation Single-Cell RNA-Sequencing Data Clustering Method Combined with a New Graph Regularization. J. Comput. Biol. 30 (8) (2023)
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)
Tian-Jing Qiao, Jin-Xing Liu, Junliang Shang, Shasha Yuan, Chun-Hou Zheng, Juan Wang
A Personalized Low-Rank Subspace Clustering Method Based on Locality and Similarity Constraints for scRNA-seq Data Analysis. IEEE J. Biomed. Health Informatics 27 (5) (2023)
He-Ming Chu, Xiang-Zhen Kong, Jin-Xing Liu, Chun-Hou Zheng, Han Zhang
A New Binary Biclustering Algorithm Based on Weight Adjacency Difference Matrix for Analyzing Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 20 (5) (2023)
Xu Wang, Ling-Yun Dai, Jin-Xing Liu, Shuang Wang
MLQP: A Machine Learning Based Quadratic Prediction Method for MiRNA-Disease Associations. BIBM (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)
Shasha Yuan, Xiang Liu, Junliang Shang, Jin-Xing Liu, Juan Wang, Weidong Zhou
Automatic Seizure Detection Using Logarithmic Euclidean-Gaussian Mixture Models (LE-GMMs) and Improved Deep Forest Learning. IEEE J. Biomed. Health Informatics 27 (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)
Juan Wang, Lin-Ping Wang, Shasha Yuan, Feng Li, Jin-Xing Liu, Junliang Shang
NLRRC: A Novel Clustering Method of Jointing Non-Negative LRR and Random Walk Graph Regularized NMF for Single-Cell Type Identification. IEEE J. Biomed. Health Informatics 27 (10) (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)
Jie Xu, Juan Wang, Jin-Xing Liu, Junliang Shang, Lingyun Dai, Kuiting Yan, Shasha Yuan
Epileptic Seizure Detection Based on Feature Extraction and CNN-BiGRU Network with Attention Mechanism. ICIC (2) (2023)
Qianqian Ren, Yahan Li, Feng Li, Jin-Xing Liu, Junliang Shang
ABCAE: Artificial Bee Colony Algorithm with Adaptive Exploitation for Epistatic Interaction Detection. ISBRA (2023)
Feng Zhou, Meng-Meng Yin, Jing-Xiu Zhao, Junliang Shang, Jin-Xing Liu
A Method Based On Dual-Network Information Fusion to Predict MiRNA-Disease Associations. IEEE ACM Trans. Comput. Biol. Bioinform. 20 (1) (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)
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)
Juan Wang, Na-Na Zhang, Junliang Shang, Jin-Xing Liu
scNMF-Impute: imputation for single-cell RNA-seq data based on nonnegative matrix factorization. BIBM (2023)
Qian Qiao, Shasha Yuan, Junliang Shang, Jin-Xing Liu
Multi-View Enhanced Tensor Nuclear Norm and Local Constraint Model for Cancer Clustering and Feature Gene Selection. J. Comput. Biol. 30 (8) (2023)
Junliang Shang, Xuhui Zhu, Yan Sun, Feng Li, Xiangzhen Kong, Jin-Xing Liu
DM-MOGA: a multi-objective optimization genetic algorithm for identifying disease modules of non-small cell lung cancer. BMC Bioinform. 24 (1) (2023)
Lin-Ping Wang, Jin-Xing Liu, Junliang Shang, Xiangzhen Kong, Boxin Guan, Juan Wang
KGLRR: A low-rank representation K-means with graph regularization constraint method for Single-cell type identification. Comput. Biol. Chem. 104 (2023)
Junliang Shang, Qi Zou, Qianqian Ren, Boxin Guan, Feng Li, Jin-Xing Liu, Yan Sun
GCCN: Graph Capsule Convolutional Network for Progressive Mild Cognitive Impairment Prediction and Pathogenesis Identification Based on Imaging Genetic Data. IEEE J. Biomed. Health Informatics 27 (6) (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)
Yahan Li, Mingrui Zhang, Junliang Shang, Yaxuan Zhang, Feng Li, Jin-Xing Liu
idenLD-AREL: identifying lncRNA-disease associations by random forests based on an ensemble learning framework. BIBM (2023)
Feng Zhou, Meng-Meng Yin, Cui-Na Jiao, Jing-Xiu Zhao, Chun-Hou Zheng, Jin-Xing Liu
Predicting miRNA-Disease Associations Through Deep Autoencoder With Multiple Kernel Learning. IEEE Trans. Neural Networks Learn. Syst. 34 (9) (2023)
Zhensheng Sun, Junliang Shang, Hongyu Duan, Jin-Xing Liu, Xikui Liu, Yan Li, Feng Li
Construction of Gene Network Based on Inter-tumor Heterogeneity for Tumor Type Identification. ICIC (2) (2022)
He-Ming Chu, Jin-Xing Liu, Ke Zhang, Chun-Hou Zheng, Juan Wang, Xiang-Zhen Kong
A binary biclustering algorithm based on the adjacency difference matrix for gene expression data analysis. BMC Bioinform. 23 (1) (2022)
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)
Cui-Na Jiao, Chun-Hou Zheng, Jin-Xing Liu, Feng Li
Probability Connectivity-Based Multimodality Regression Analysis for Associating Disease-Specific Multimodal Brain Imaging Phenotypes with Genetic Risk Factors. 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)
Qi Zou, Yan Sun, Feng Li, Juan Wang, Jin-Xing Liu, Junliang Shang
TDCOSR: A Multimodality Fusion Framework for Association Analysis Between Genes and ROIs of Alzheimer's Disease. ISBRA (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)
Juan Wang, Li-Hong Wang, Jin-Xing Liu, Xiang-Zhen Kong, Shengjun Li
Multi-View Random-Walk Graph Regularization Low-Rank Representation for Cancer Clustering and Differentially Expressed Gene Selection. IEEE J. Biomed. Health Informatics 26 (7) (2022)
Sheng-Nan Zhang, Yu-Lin Zhang, Jin-Xing Liu, Juan Wang, Junliang Shang, Dao-Hui Ge
Tensor Robust PCA Based on Transformed Tensor Singular Value Decomposition for Cancer Genomic Data. 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)
Zhen-Chang Wang, Jin-Xing Liu, Junliang Shang, Ling-Yun Dai, Chun-Hou Zheng, Juan Wang
ARGLRR: An Adjusted Random Walk Graph Regularization Sparse Low-Rank Representation Method for Single-Cell RNA-Sequencing Data Clustering. ISBRA (2022)
XinChu, Feng Li, Hongyu Duan, Junliang Shang, Juan Wang, Jin-Xing Liu
Identification of cancer driver modules by combining network functional and topology information. BIBM (2022)
Zhen-Xin Niu, Cui-Na Jiao, Liang-Rui Ren, Rong Zhu, Juan Wang, Jin-Xing Liu
Kernel risk-sensitive mean p-power loss based hyper-graph regularized robust extreme learning machine and its semi-supervised extension for sample classification. Appl. Intell. 52 (8) (2022)
Han Han, Rong Zhu, Jin-Xing Liu, Ling-Yun Dai
Predicting miRNA-disease associations via layer attention graph convolutional network model. BMC Medical Informatics Decis. Mak. 22 (1) (2022)
Na-Na Zhang, Jin-Xing Liu, Chun-Hou Zheng, Juan Wang
SLRRSC: Single-Cell Type Recognition Method Based on Similarity and Graph Regularization Constraints. IEEE J. Biomed. Health Informatics 26 (7) (2022)
Cui-Na Jiao, Jin-Xing Liu, Juan Wang, Junliang Shang, Chun-Hou Zheng
Visualization and Analysis of Single Cell RNA-Seq Data by Maximizing Correntropy Based Non-Negative Low Rank Representation. IEEE J. Biomed. Health Informatics 26 (4) (2022)
Tian-Ru Wu, Cui-Na Jiao, Xin-Chun Cui, Jin-Xing Liu
Diagnosing Alzheimer's Disease with Bi-multitask Regularized Sparse Canonical Correlation Analysis and Logistic Regression. BIBM (2022)
Qian Qiao, Shasha Yuan, Junliang Shang, Jin-Xing Liu
A Tensor Robust Model Based on Enhanced Tensor Nuclear Norm and Low-Rank Constraint for Multi-view Cancer Genomics Data. ISBRA (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)
Delu Ma, Shasha Yuan, Junliang Shang, Jin-Xing Liu, Lingyun Dai, Xiangzhen Kong, Fangzhou Xu
The Automatic Detection of Seizure Based on Tensor Distance And Bayesian Linear Discriminant Analysis. Int. J. Neural Syst. 31 (5) (2021)
He-Ming Chu, Xiang-Zhen Kong, Jin-Xing Liu, Juan Wang, Shasha Yuan, Ling-Yun Dai
Joint CC and Bimax: A Biclustering Method for Single-Cell RNA-Seq Data Analysis. ISBRA (2021)
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)
Ling-Yun Dai, Jin-Xing Liu, Rong Zhu, Juan Wang, Shasha Yuan
Logistic Weighted Profile-Based Bi-Random Walk for Exploring MiRNA-Disease Associations. J. Comput. Sci. Technol. 36 (2) (2021)
Na Yu, Ming-Juan Wu, Jin-Xing Liu, Chun-Hou Zheng, Yong Xu
Correntropy-Based Hypergraph Regularized NMF for Clustering and Feature Selection on Multi-Cancer Integrated Data. IEEE Trans. Cybern. 51 (8) (2021)
Rong Zhu, Yong Wang, Jin-Xing Liu, Ling-Yun Dai
IPCARF: improving lncRNA-disease association prediction using incremental principal component analysis feature selection and a random forest classifier. BMC Bioinform. 22 (1) (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)
Junliang Shang, Jing Wang, Yan Sun, Feng Li, Jin-Xing Liu, Honghai Zhang
Multiscale part mutual information for quantifying nonlinear direct associations in networks. Bioinform. 37 (18) (2021)
Feng Zhou, Meng-Meng Yin, Cui-Na Jiao, Zhen Cui, Jing-Xiu Zhao, Jin-Xing Liu
Bipartite graph-based collaborative matrix factorization method for predicting miRNA-disease associations. BMC Bioinform. 22 (1) (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)
Ke Yan, Jie Wen, Jin-Xing Liu, Yong Xu, Bin Liu
Protein Fold Recognition by Combining Support Vector Machines and Pairwise Sequence Similarity Scores. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (5) (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)
Junliang Shang, Yiting Li, Yan Sun, Feng Li, Yuanyuan Zhang, Jin-Xing Liu
MOPIO: A Multi-Objective Pigeon-Inspired Optimization Algorithm for Community Detection. Symmetry 13 (1) (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)
Chang-Gang Wen, Jin-Xing Liu, Lei Qin, Juan Wang, Yun Fang
Essential Proteins Identification Based on Integrated Network. ICIC (1) (2020)
Juan Wang, Jin-Xing Liu, Chun-Hou Zheng, Cong-Hai Lu, Ling-Yun Dai, Xiang-Zhen Kong
Block-Constraint Laplacian-Regularized Low-Rank Representation and Its Application for Cancer Sample Clustering Based on Integrated TCGA Data. Complex. 2020 (2020)
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)
Hang-Jin Yang, Yu-Ying Zhao, Jin-Xing Liu, Yuxia Lei, Junliang Shang, Xiang-Zhen Kong
Sparse Regularization Tensor Robust PCA Based on t-product and Its Application in Cancer Genomic Data. BIBM (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)
Shasha Yuan, Jin-Xing Liu, Junliang Shang, Fangzhou Xu, Lingyun Dai, Xiangzhen Kong
Automatic Seizure Prediction based on Modified Stockwell Transform and Tensor Decomposition. BIBM (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)
Wenwen Fan, Junliang Shang, Feng Li, Yan Sun, Shasha Yuan, Jin-Xing Liu
IDSSIM: an lncRNA functional similarity calculation model based on an improved disease semantic similarity method. BMC Bioinform. 21 (1) (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)
Yu-Ying Zhao, Mao-Li Wang, Juan Wang, Shasha Yuan, Jin-Xing Liu, Xiang-Zhen Kong
Tensor Robust Principal Component Analysis with Low-Rank Weight Constraints for Sample Clustering. BIBM (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)
Yingxia Sun, Xuan Wang, Junliang Shang, Jin-Xing Liu, Chun-Hou Zheng, Xiujuan Lei
Introducing Heuristic Information Into Ant Colony Optimization Algorithm for Identifying Epistasis. IEEE ACM Trans. Comput. Biol. Bioinform. 17 (4) (2020)
Ya-Li Zhu, Ming-Juan Wu, Chuan-Yuan Wang, Yue Hu, Jin-Xing Liu
Adaptive Total Variation Constraint Hypergraph Regularized NMF and Its Application on Single-Cell RNA-Seq Data. BIC-TA (2020)
Yu Song, Xiang-Zhen Kong, Jin-Xing Liu, Juan Wang, Shasha Yuan, Ling-Yun Dai
Dual Graph regularized PCA based on Different Norm Constraints for Bi-clustering Analysis on Single-cell RNA-seq Data. 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)
Ling-Yun Dai, Chun-Hou Zheng, Jin-Xing Liu, Rong Zhu, Shasha Yuan, Juan Wang, Xiang-Zhen Kong
Integrative graph regularized matrix factorization for drug-pathway associations analysis. Comput. Biol. Chem. 78 (2019)

Jin-Xing Liu.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Jin-Xing Liu