default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJin-Xing Liu 0001
Jin-Xin Liu 0001 – Jinxing Liu 0001
Person information
- affiliation: University of Health and Rehabilitation Sciences, Qingdao, China
- affiliation: Qufu Normal University, School of Computer Science, Rizhao, China
- affiliation (2011 - 2015): Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, China
- affiliation (PhD 2008): South China University of Technology, State Key Laboratory of Pulp and Paper Engineering, Guangzhou, China
Other persons with the same name
- Jin-Xing Liu (aka: Jin-Xin Liu) — disambiguation page
- Jinxing Liu — disambiguation page
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
Journal Articles
- 2024
[j113]Feng Li, Yang Liu, Jinxing Liu, Daohui Ge, Junliang Shang:
A framework for scRNA-seq data clustering based on multi-view feature integration. Biomed. Signal Process. Control. 89: 105785 (2024)- [j112]Cui-Na Jiao
, Ying-Lian Gao, Dao-Hui Ge, Junliang Shang, Jin-Xing Liu:
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. 130: 107782 (2024) - [j111]Yuxia Wang, Shasha Yuan, Jin-Xing Liu, Wenrong Hu, Qingwei Jia, Fangzhou Xu:
Combining EEG Features and Convolutional Autoencoder for Neonatal Seizure Detection. Int. J. Neural Syst. 34(8): 2450040:1-2450040:13 (2024) - [j110]Qianqian Ren, Lianlian Zhang, Shaoyi Liu, Jin-Xing Liu, Junliang Shang, Xiyu Liu:
A Delayed Spiking Neural Membrane System for Adaptive Nearest Neighbor-Based Density Peak Clustering. Int. J. Neural Syst. 34(10): 2450050:1-2450050:15 (2024) - [j109]Yue Gao, Ying-Lian Gao, Jing Jing, Feng Li, Chun-Hou Zheng, Jin-Xing Liu:
A review of recent advances in spatially resolved transcriptomics data analysis. Neurocomputing 603: 128283 (2024) - [j108]Jie Xu, Kuiting Yan, Zengqian Deng, Yankai Yang, Jin-Xin Liu, Juan Wang, Shasha Yuan:
EEG-based epileptic seizure detection using deep learning techniques: A survey. Neurocomputing 610: 128644 (2024) - [j107]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: 111187 (2024) - [j106]Yahan Li, Xinrui Cai, Junliang Shang, Yuanyuan Zhang, Jin-Xing Liu:
SimHOEPI: A resampling simulator for generating single nucleotide polymorphism data with a high-order epistasis model. Quant. Biol. 12(2): 197-204 (2024) - [j105]Juan Wang, Zhen-Chang Wang, Shasha Yuan, Chun-Hou Zheng, Jin-Xing Liu, Junliang Shang:
A Clustering Method for Single-Cell RNA-Seq Data Based on Automatic Weighting Penalty and Low-Rank Representation. IEEE ACM Trans. Comput. Biol. Bioinform. 21(3): 360-371 (2024) - [j104]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: 1-11 (2024) - [j103]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): 1110-1121 (2024) - [j102]Cui-Na Jiao, Junliang Shang, Feng Li, Xinchun Cui, Yan-Li Wang, Ying-Lian Gao, Jin-Xing Liu:
Diagnosis-Guided Deep Subspace Clustering Association Study for Pathogenetic Markers Identification of Alzheimer's Disease Based on Comparative Atlases. IEEE J. Biomed. Health Informatics 28(5): 3029-3041 (2024) - [j101]Wen-Yue Kang, Ying-Lian Gao, Ying Wang, Feng Li, Jin-Xing Liu:
KFDAE: CircRNA-Disease Associations Prediction Based on Kernel Fusion and Deep Auto-Encoder. IEEE J. Biomed. Health Informatics 28(5): 3178-3185 (2024) - [j100]Tian-Ru Wu, Cui-Na Jiao, Xinchun Cui, Yan-Li Wang, Chun-Hou Zheng, Jin-Xing Liu:
Deep Self-Reconstruction Fusion Similarity Hashing for the Diagnosis of Alzheimer's Disease on Multi-Modal Data. IEEE J. Biomed. Health Informatics 28(6): 3513-3522 (2024) - [j99]Qi Zhong, Junliang Shang, Qianqian Ren, Feng Li, Cui-Na Jiao, Jin-Xing Liu:
FSCME: A Feature Selection Method Combining Copula Correlation and Maximal Information Coefficient by Entropy Weights. IEEE J. Biomed. Health Informatics 28(9): 5638-5648 (2024) - [j98]Shuang Wang, Jin-Xing Liu, Feng Li, Juan Wang, Ying-Lian Gao:
M3HOGAT: A Multi-View Multi-Modal Multi-Scale High-Order Graph Attention Network for Microbe-Disease Association Prediction. IEEE J. Biomed. Health Informatics 28(10): 6259-6267 (2024) - [j97]Junliang Shang, Linqian Zhao, Xin He, Xianghan Meng, Limin Zhang, Daohui Ge, Feng Li, Jin-Xing Liu:
SGFCCDA: Scale Graph Convolutional Networks and Feature Convolution for circRNA-Disease Association Prediction. IEEE J. Biomed. Health Informatics 28(11): 7006-7014 (2024) - [j96]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): 2473-2483 (2024) - [j95]Yi Yang, Yan Sun, Feng Li, Boxin Guan, Jin-Xing Liu, Junliang Shang:
MGCNRF: Prediction of Disease-Related miRNAs Based on Multiple Graph Convolutional Networks and Random Forest. IEEE Trans. Neural Networks Learn. Syst. 35(11): 15701-15709 (2024) - 2023
- [j94]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): 13 (2023) - [j93]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: 107862 (2023) - [j92]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): 848-860 (2023) - [j91]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): 889-899 (2023) - [j90]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): 926-936 (2023) - [j89]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): 937-947 (2023) - [j88]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): 52-60 (2023) - [j87]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): 534-543 (2023) - [j86]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): 1774-1782 (2023) - [j85]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): 2802-2809 (2023) - [j84]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): 3737-3747 (2023) - [j83]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): 1386-1396 (2023) - [j82]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): 1644-1653 (2023) - [j81]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): 2575-2584 (2023) - [j80]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): 2968-2979 (2023) - [j79]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): 3686-3694 (2023) - [j78]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): 5187-5198 (2023) - [j77]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): 5199-5209 (2023) - [j76]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): 5570-5579 (2023) - 2022
- [j75]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): 8572-8587 (2022) - [j74]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) - [j73]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): 381 (2022) - [j72]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: 247-255 (2022) - [j71]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): 2250002:1-2250002:20 (2022) - [j70]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): 69 (2022) - [j69]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): 199-216 (2022) - [j68]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): 1154-1164 (2022) - [j67]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): 2420-2430 (2022) - [j66]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): 5079-5087 (2022) - [j65]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): 458-467 (2022) - [j64]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): 1872-1882 (2022) - [j63]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): 3556-3566 (2022) - [j62]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): 3578-3589 (2022) - 2021
- [j61]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): 2920-2929 (2021) - [j60]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): 175 (2021) - [j59]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): 573 (2021) - [j58]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. 22-S(3): 241 (2021) - [j57]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): 2150006:1-2150006:15 (2021) - [j56]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): 2050047:1-2050047:24 (2021) - [j55]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): 276-287 (2021) - [j54]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: 107226 (2021) - [j53]Ya-li Zhu, Xiao-ning Zhang, Chuan-Yuan Wang, Jin-Xing Liu, Xiangzhen Kong:
Adaptive total variation constraint hypergraph regularized NMF for single-cell RNA-seq data analysis. Quant. Biol. 9(4): 451-462 (2021) - [j52]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): 49 (2021) - [j51]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): 1122-1129 (2021) - [j50]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): 1481-1491 (2021) - [j49]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): 2008-2016 (2021) - [j48]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): 2375-2383 (2021) - [j47]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): 3952-3963 (2021) - [j46]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): 257-265 (2021) - [j45]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): 881-890 (2021) - 2020
- [j44]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): 339 (2020) - [j43]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): 445 (2020) - [j42]Tian-Ru 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): 454 (2020) - [j41]Liang-Rui Ren, Ying-Lian Gao, Jin-Xing Liu, Rong Zhu, Xiang-Zhen Kong:
L2, 1-Extreme Learning Machine: An Efficient Robust Classifier for Tumor Classification. Comput. Biol. Chem. 89: 107368 (2020) - [j40]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: 4865738:1-4865738:13 (2020) - [j39]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): 140-159 (2020) - [j38]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): 1253-1261 (2020) - [j37]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): 1519-1527 (2020) - [j36]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): 1823-1834 (2020) - [j35]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): 3002-3011 (2020) - 2019
- [j34]Junliang Shang, Xuan Wang, Xiaoyang Wu, Yingxia Sun, Qian Ding, Jin-Xing Liu, Honghai Zhang:
A Review of Ant Colony Optimization Based Methods for Detecting Epistatic Interactions. IEEE Access 7: 13497-13509 (2019) - [j33]Ying-Lian Gao, Mi-Xiao Hou, Jin-Xing Liu, Xiang-Zhen Kong:
An Integrated Graph Regularized Non-Negative Matrix Factorization Model for Gene Co-Expression Network Analysis. IEEE Access 7: 126594-126602 (2019) - [j32]Qian Ding, Junliang Shang, Yan Sun, Guangshuai Liu, Feng Li, Xiguo Yuan, Jin-Xing Liu:
NIPMI: A Network Method Based on Interaction Part Mutual Information to Detect Characteristic Genes From Integrated Data on Multi-Cancers. IEEE Access 7: 135845-135854 (2019) - [j31]Jin-Xing Liu, Chun-Mei Feng, Xiang-Zhen Kong, Yong Xu:
Dual Graph-Laplacian PCA: A Closed-Form Solution for Bi-Clustering to Find "Checkerboard" Structures on Gene Expression Data. IEEE Access 7: 151329-151338 (2019) - [j30]Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang, Ling-Yun Dai:
The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method. BMC Bioinform. 20(1): 5 (2019) - [j29]Rong Zhu, Guangshun Li, Jin-Xing Liu, Ling-Yun Dai, Ying Guo:
ACCBN: ant-Colony-clustering-based bipartite network method for predicting long non-coding RNA-protein interactions. BMC Bioinform. 20(1): 16 (2019) - [j28]Ying-Lian Gao, Zhen Cui, Jin-Xing Liu, Juan Wang, Chun-Hou Zheng:
NPCMF: Nearest Profile-based Collaborative Matrix Factorization method for predicting miRNA-disease associations. BMC Bioinform. 20(1): 353:1-353:10 (2019) - [j27]Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Shasha Yuan:
L2, 1-GRMF: an improved graph regularized matrix factorization method to predict drug-target interactions. BMC Bioinform. 20-S(8): 287:1-287:13 (2019) - [j26]Juan Wang, Cong-Hai Lu, Jin-Xing Liu, Ling-Yun Dai, Xiang-Zhen Kong:
Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints. BMC Bioinform. 20-S(22): 718 (2019) - [j25]Zhen Cui, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Juan Wang:
RCMF: a robust collaborative matrix factorization method to predict miRNA-disease associations. BMC Bioinform. 20-S(25): 686 (2019) - [j24]Qian Ding, Junliang Shang, Yingxia Sun, Xuan Wang, Jin-Xing Liu:
HC-HDSD: A method of hypergraph construction and high-density subgraph detection for inferring high-order epistatic interactions. Comput. Biol. Chem. 78: 440-447 (2019) - [j23]Mi-Xiao Hou, Ying-Lian Gao, Jin-Xing Liu, Ling-Yun Dai, Xiang-Zhen Kong, Junliang Shang:
Network analysis based on low-rank method for mining information on integrated data of multi-cancers. Comput. Biol. Chem. 78: 468-473 (2019) - [j22]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: 474-480 (2019) - [j21]Juan Wang, Jin-Xing Liu, Xiang-Zhen Kong, Shasha Yuan, Ling-Yun Dai:
Laplacian regularized low-rank representation for cancer samples clustering. Comput. Biol. Chem. 78: 504-509 (2019) - [j20]Yue Hu, Jin-Xing Liu, Ying-Lian Gao, Shengjun Li, Juan Wang:
Differentially Expressed Genes Extracted by the Tensor Robust Principal Component Analysis (TRPCA) Method. Complex. 2019: 6136245:1-6136245:13 (2019) - [j19]Yong-Jing Hao, Ying-Lian Gao, Mi-Xiao Hou, Ling-Yun Dai, Jin-Xing Liu:
Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection. Complex. 2019: 7081674:1-7081674:12 (2019) - [j18]Huiyu Li, Shengjun Li, Junliang Shang, Jin-Xing Liu, Chun-Hou Zheng:
A Dynamic Scale-Free Network Particle Swarm Optimization for Extracting Features on Multi-Omics Data. J. Comput. Biol. 26(8): 769-781 (2019) - [j17]Juan Wang, Jin-Xing Liu, Chun-Hou Zheng, Yaxuan Wang, Xiang-Zhen Kong, Chang-Gang Wen:
A Mixed-Norm Laplacian Regularized Low-Rank Representation Method for Tumor Samples Clustering. IEEE ACM Trans. Comput. Biol. Bioinform. 16(1): 172-182 (2019) - [j16]Chun-Mei Feng, Yong Xu, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng:
Supervised Discriminative Sparse PCA for Com-Characteristic Gene Selection and Tumor Classification on Multiview Biological Data. IEEE Trans. Neural Networks Learn. Syst. 30(10): 2926-2937 (2019) - 2018
- [j15]Jin-Xing Liu, Dong Wang, Ying-Lian Gao, Chun-Hou Zheng, Yong Xu, Jiguo Yu:
Regularized Non-Negative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Samples: A Survey. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 974-987 (2018) - 2017
- [j14]Yingxia Sun, Junliang Shang, Jin-Xing Liu, Shengjun Li, Chun-Hou Zheng:
epiACO - a method for identifying epistasis based on ant Colony optimization algorithm. BioData Min. 10(1): 23:1-23:17 (2017) - [j13]Jin-Xing Liu, Dong-Qin Wang, Chun-Hou Zheng, Ying-Lian Gao, Sha-Sha Wu, Junliang Shang:
Identifying drug-pathway association pairs based on L2, 1-integrative penalized matrix decomposition. BMC Syst. Biol. 11(6): 63-73 (2017) - [j12]Ling-Yun Dai, Chun-Mei Feng, Jin-Xing Liu, Chun-Hou Zheng, Jiguo Yu, Mi-Xiao Hou:
Robust Nonnegative Matrix Factorization via Joint Graph Laplacian and Discriminative Information for Identifying Differentially Expressed Genes. Complex. 2017: 4216797:1-4216797:11 (2017) - [j11]Xiu-Xiu Xu, Ying-Lian Gao, Jin-Xing Liu, Yaxuan Wang, Ling-Yun Dai, Xiang-Zhen Kong, Shasha Yuan:
A novel low-rank representation method for identifying differentially expressed genes. Int. J. Data Min. Bioinform. 19(3): 185-201 (2017) - [j10]Jin-Xing Liu, Dong Wang, Ying-Lian Gao, Chun-Hou Zheng, Junliang Shang, Feng Liu, Yong Xu:
A joint-L2, 1-norm-constraint-based semi-supervised feature extraction for RNA-Seq data analysis. Neurocomputing 228: 263-269 (2017) - 2016
- [j9]Junliang Shang, Yingxia Sun, Jin-Xing Liu, Junfeng Xia, Junying Zhang, Chun-Hou Zheng:
CINOEDV: a co-information based method for detecting and visualizing n-order epistatic interactions. BMC Bioinform. 17: 214 (2016) - [j8]Yaxuan Wang, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Junliang Shang:
Differentially expressed genes selection via Laplacian regularized low-rank representation method. Comput. Biol. Chem. 65: 185-192 (2016) - [j7]Shengjun Li, Junliang Shang, Qinliang Chen, Yan Sun, Jin-Xing Liu:
A compressed sensing based two-stage method for detecting epistatic interactions. Int. J. Data Min. Bioinform. 14(4): 354-372 (2016) - [j6]Jin-Xing Liu, Yong Xu, Ying-Lian Gao, Chun-Hou Zheng, Dong Wang, Qi Zhu:
A Class-Information-Based Sparse Component Analysis Method to Identify Differentially Expressed Genes on RNA-Seq Data. IEEE ACM Trans. Comput. Biol. Bioinform. 13(2): 392-398 (2016) - [j5]Dong Wang, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Yong Xu:
Characteristic Gene Selection Based on Robust Graph Regularized Non-Negative Matrix Factorization. IEEE ACM Trans. Comput. Biol. Bioinform. 13(6): 1059-1067 (2016) - 2015
- [j4]Jin-Xing Liu, Yong Xu, Chun-Hou Zheng, Heng Kong, Zhihui Lai:
RPCA-Based Tumor Classification Using Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 12(4): 964-970 (2015) - 2013
- [j3]Jin-Xing Liu, Yutian Wang, Chun-Hou Zheng, Wen Sha, Jian-Xun Mi, Yong Xu:
Robust PCA based method for discovering differentially expressed genes. BMC Bioinform. 14(S-8): S3 (2013) - 2012
- [j2]Jin-Xing Liu, Chun-Hou Zheng, Yong Xu:
Extracting plants core genes responding to abiotic stresses by penalized matrix decomposition. Comput. Biol. Medicine 42(5): 582-589 (2012) - 2011
- [j1]Jun Zhang, Chun-Hou Zheng, Jin-Xing Liu, Hong-Qiang Wang:
Discovering the transcriptional modules using microarray data by penalized matrix decomposition. Comput. Biol. Medicine 41(11): 1041-1050 (2011)
Conference and Workshop Papers
- 2024
- [c84]Junliang Shang, Limin Zhang, Linqian Zhao, Xin He, Yan Zhao, Daohui Ge, Jin-Xing Liu, Feng Li:
SGEGCAE: A Sparse Gating Enhanced Graph Convolutional Autoencoder for Multi-omics Data Integration and Classification. ICIC (LNBI 1) 2024: 135-146 - [c83]Jing Jing, Ying-Lian Gao, Yue Gao, Dao-Hui Ge, Chun-Hou Zheng, Jin-Xing Liu:
stMCFN: A Multi-view Contrastive Fusion Method for Spatial Domain Identification in Spatial Transcriptomics. ICIC (LNBI 1) 2024: 321-331 - [c82]Wenrong Hu, Junliang Shang, Juan Wang, Jin-Xing Liu, Yuxia Wang, Shasha Yuan:
Automatic Seizure Recognition Based on Data Enhancement and 1DCNN-BiLSTM Network Using EEG Signal. ICIC (LNBI 1) 2024: 370-379 - [c81]Qingwei Jia, Jin-Xing Liu, Junling Shang, Lingyun Dai, Yuxia Wang, Wenrong Hu, Shasha Yuan:
Seizure Types Classification Based on Multi-branch Hybrid Deep Learning Network. ICIC (4) 2024: 462-474 - [c80]Junliang Shang, Yahan Li, Xiaohan Zhang, Feng Li, Yuanyuan Zhang, Jin-Xing Liu:
CPSORCL: A Cooperative Particle Swarm Optimization Method with Random Contrastive Learning for Interactive Feature Selection. ISBRA (2) 2024: 327-338 - [c79]Shuang-Qing Wang, Cui-Na Jiao, Tian-Ru Wu, Xinchun Cui, Chun-Hou Zheng, Jin-Xing Liu:
Deep Hyper-Laplacian Regularized Self-representation Learning Based Structured Association Analysis for Brain Imaging Genetics. ISBRA (1) 2024: 418-426 - 2023
- [c78]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: 233-236 - [c77]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: 648-653 - [c76]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: 2769-2776 - [c75]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: 3200-3207 - [c74]Xu Wang, Ling-Yun Dai, Jin-Xing Liu, Shuang Wang:
MLQP: A Machine Learning Based Quadratic Prediction Method for MiRNA-Disease Associations. BIBM 2023: 3208-3211 - [c73]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: 291-299 - [c72]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: 308-319 - [c71]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: 359-367 - [c70]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: 190-201 - 2022
- [c69]Junliang Shang, Yijun Gu, Yan Sun, Feng Li, Jin-Xin Liu, Boxin Guan:
Artificial bee colony algorithm based on self-adjusting random grouping for high-order epistasis detection. BIBM 2022: 549-554 - [c68]Wen-Yu Xi, Qianqian Ren, Jin-Xing Liu, Ying-Lian Gao:
HSAELDA: Predicting lncRNA-disease associations based on heterogeneous networks and Stacked Autoencoder. BIBM 2022: 607-612 - [c67]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: 1034-1039 - [c66]Tian-Ru Wu, Cui-Na Jiao, Xinchun Cui, Jin-Xing Liu:
Diagnosing Alzheimer's Disease with Bi-multitask Regularized Sparse Canonical Correlation Analysis and Logistic Regression. BIBM 2022: 1268-1273 - [c65]Zhi-Yuan Li, Ying-Lian Gao, Zhen-Xin Niu, Shasha 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: 2088-2094 - [c64]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: 2162-2168 - [c63]Xin Chu, 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: 2832-2838 - [c62]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: 345-355 - [c61]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: 1-8 - [c60]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: 126-137 - [c59]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: 159-168 - [c58]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: 295-302 - [c57]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: 381-388 - [c56]Tian-Jing Qiao, Na-Na Zhang, Jin-Xing Liu, Junliang Shang, Cui-Na Jiao, Juan Wang:
THSLRR: A Low-Rank Subspace Clustering Method Based on Tired Random Walk Similarity and Hypergraph Regularization Constraints. SDSC 2022: 80-93 - 2021
- [c55]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: 418-423 - [c54]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: 509-514 - [c53]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: 775-778 - [c52]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: 532-539 - [c51]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: 3-10 - [c50]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: 499-510 - 2020
- [c49]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: 92-95 - [c48]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: 121-125 - [c47]Yu-Ying Zhao, Maoli 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: 397-401 - [c46]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: 1503-1509 - [c45]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: 2131-2138 - [c44]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: 17-24 - [c43]Chang-Gang Wen, Jin-Xing Liu, Lei Qin, Juan Wang, Yun Fang:
Essential Proteins Identification Based on Integrated Network. ICIC (1) 2020: 81-91 - [c42]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: 537-545 - 2019
- [c41]Ming-Ming Gao, Zhen Cui, Ying-Lian Gao, Feng Li, Jin-Xing Liu:
Dual Sparse Collaborative Matrix Factorization Method Based on Gaussian Kernel Function for Predicting LncRNA-Disease Associations. ICIC (3) 2019: 318-326 - [c40]Yong-Jing Hao, Mi-Xiao Hou, Rong Zhu, Jin-Xing Liu:
An Integrated Robust Graph Regularized Non-negative Matrix Factorization for Multi-dimensional Genomic Data Analysis. IDMB 2019: 97-111 - [c39]Cui-Na Jiao, Tian-Ru Wu, Jin-Xing Liu, Xiang-Zhen Kong:
Hyper-graph Robust Non-negative Matrix Factorization Method for Cancer Sample Clustering and Feature Selection. IDMB 2019: 112-125 - [c38]Qian Ding, Yan Sun, Junliang Shang, Yuanyuan Zhang, Feng Li, Jin-Xing Liu:
Inferring Communities and Key Genes of Triple Negative Breast Cancer Based on Robust Principal Component Analysis and Network Analysis. IDMB 2019: 137-151 - [c37]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: 196-208 - 2018
- [c36]Na Yu, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang:
Hypergraph regularized NMF by L2, 1-norm for Clustering and Com-abnormal Expression Genes Selection. BIBM 2018: 578-582 - [c35]Ling-Yun Dai, Jin-Xing Liu, Rong Zhu, Xiang-Zhen Kong, Mi-Xiao Hou, Shasha Yuan:
Sparse Orthogonal Nonnegative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Tumor Samples. BIBM 2018: 1332-1337 - [c34]Rong Zhu, Guangshun Li, Jin-Xing Liu, Ling-Yun Dai, Shasha Yuan, Ying Guo:
A Fast Quantum Clustering Approach for Cancer Gene Clustering. BIBM 2018: 1610-1613 - [c33]Mi-Xiao Hou, Jin-Xing Liu, Junliang Shang, Ying-Lian Gao, Xiang-Zhen Kong, Ling-Yun Dai:
Performance Analysis of Non-negative Matrix Factorization Methods on TCGA Data. ICIC (2) 2018: 407-418 - [c32]Shasha Wu, Mi-Xiao Hou, Jin-Xing Liu, Juan Wang, Shasha Yuan:
Identifying Characteristic Genes and Clustering via an Lp-Norm Robust Feature Selection Method for Integrated Data. ICIC (2) 2018: 419-431 - [c31]Chang Liu, Junliang Shang, Xuhui Zhu, Yan Sun, Jin-Xing Liu, Chun-Hou Zheng, Junying Zhang:
acsFSDPC: A Density-Based Automatic Clustering Algorithm with an Adaptive Cuckoo Search. ICIC (2) 2018: 470-482 - [c30]Huiyu Li, Shengjun Li, Junliang Shang, Jin-Xing Liu, Chun-Hou Zheng:
An Improved Particle Swarm Optimization with Dynamic Scale-Free Network for Detecting Multi-omics Features. ISBRA 2018: 26-37 - 2017
- [c29]Yaxuan Wang, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Ling-Yun Dai:
Low-rank representation regularized by L2, 1-norm for identifying differentially expressed genes. BIBM 2017: 626-629 - [c28]Ming-Juan Wu, Jin-Xing Liu, Ying-Lian Gao, Xiangzhen Kong, Chun-Mei Feng:
Feature selection and clustering via robust graph-laplacian PCA based on capped L1-norm. BIBM 2017: 1741-1745 - [c27]Na Yu, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng, Juan Wang, Ming-Juan Wu:
Graph regularized robust non-negative matrix factorization for clustering and selecting differentially expressed genes. BIBM 2017: 1752-1756 - [c26]Ling-Yun Dai, Jin-Xing Liu, Chun-Hou Zheng, Junliang Shang, Chun-Mei Feng, Yaxuan Wang:
Robust graph regularized sparse orthogonal nonnegative matrix factorization for identifying differentially expressed genes. BIBM 2017: 1900-1905 - [c25]Yao Lu, Jin-Xing Liu, Xiangzhen Kong, Junliang Shang:
A convex multi-view low-rank sparse regression for feature selection and clustering. BIBM 2017: 2183-2186 - 2016
- [c24]Xiangzhen Kong, Jin-Xing Liu, Chun-Hou Zheng, Mi-Xiao Hou, Yao Lu:
A p-norm singular value decomposition method for robust tumor clustering. BIBM 2016: 600-605 - [c23]Dong-Qin Wang, Chun-Hou Zheng, Ying-Lian Gao, Jin-Xing Liu, Sha-Sha Wu, Junliang Shang:
L21-iPaD: An efficient method for drug-pathway association pairs inference. BIBM 2016: 664-669 - [c22]Ling-Yun Dai, Chun-Mei Feng, Jin-Xing Liu, Chun-Hou Zheng, Mi-Xiao Hou, Jiguo Yu:
Robust graph regularized discriminative nonnegative matrix factorization for characteristic gene selection. BIBM 2016: 1253-1258 - [c21]Chun-Mei Feng, Jin-Xing Liu, Ying-Lian Gao, Juan Wang, Dong-Qin Wang, Yong Du:
A graph-Laplacian PCA based on L1/2-norm constraint for characteristic gene selection. BIBM 2016: 1795-1799 - [c20]Jin-Xing Liu, Xiangzhen Kong, Chun-Hou Zheng, Junliang Shang, Wei Zhang:
Sparse singular value decomposition-based feature extraction for identifying differentially expressed genes. BIBM 2016: 1822-1827 - [c19]Yao Lu, Ying-Lian Gao, Jin-Xing Liu, Chang-Gang Wen, Yaxuan Wang, Jiguo Yu:
Characteristic gene selection via L2, 1-norm Sparse Principal Component Analysis. BIBM 2016: 1828-1833 - [c18]Yaxuan Wang, Jin-Xing Liu, Ying-Lian Gao, Xiangzhen Kong, Chun-Hou Zheng, Yong Du:
Differentially expressed genes selection via Truncated Nuclear Norm Regularization. BIBM 2016: 1851-1855 - [c17]Tianqi Wang, Ke Yan, Yong Xu, Jin-Xing Liu:
An Adaptive Weighted Degree Kernel to Predict the Splice Site. CCBR 2016: 739-746 - [c16]Yingxia Sun, Junliang Shang, Jin-Xing Liu, Shengjun Li:
An Improved Ant Colony Optimization Algorithm for the Detection of SNP-SNP Interactions. ICIC (3) 2016: 21-32 - [c15]Shengjun Li, Junliang Shang, Jin-Xing Liu, Huiyu Li:
A Compressed Sensing Based Feature Extraction Method for Identifying Characteristic Genes. ICIC (2) 2016: 67-77 - [c14]Wenxiang Zhang, Junliang Shang, Huiyu Li, Yingxia Sun, Jin-Xing Liu:
SIPSO: Selectively Informed Particle Swarm Optimization Based on Mutual Information to Determine SNP-SNP Interactions. ICIC (1) 2016: 112-121 - [c13]Xiangzhen Kong, Jin-Xing Liu, Chun-Hou Zheng, Junliang Shang:
Gene Extraction Based on Sparse Singular Value Decomposition. ICIC (1) 2016: 285-293 - [c12]Mi-Xiao Hou, Ying-Lian Gao, Jin-Xing Liu, Junliang Shang, Chun-Hou Zheng:
Comparison of Non-negative Matrix Factorization Methods for Clustering Genomic Data. ICIC (2) 2016: 290-299 - [c11]Chun-Mei Feng, Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng, Shengjun Li, Dong Wang:
A Simple Review of Sparse Principal Components Analysis. ICIC (2) 2016: 374-383 - 2015
- [c10]Ke Yan, Jin-Xing Liu, Yong Xu:
An Improved Denoising Method Based on Wavelet Transform for Processing Bases Sequence Images. ICIC (1) 2015: 357-365 - [c9]Xiao-Dan Wang, Jin-Xing Liu, Yong Xu, Jian Zhang:
A Survey of Multiple Sequence Alignment Techniques. ICIC (1) 2015: 529-538 - [c8]Ying-Lian Gao, Jin-Xing Liu, Chun-Hou Zheng, Shengjun Li, Yuxia Lei:
A Two-Stage Sparse Selection Method for Extracting Characteristic Genes. ICIC (2) 2015: 577-588 - [c7]Dong Wang, Ying-Lian Gao, Jin-Xing Liu, Jiguo Yu, Chang-Gang Wen:
Application of Graph Regularized Non-negative Matrix Factorization in Characteristic Gene Selection. ICIC (2) 2015: 601-611 - [c6]Chun-Xia Ma, Ying-Lian Gao, Dong Wang, Jian Liu, Jin-Xing Liu:
Graph Regularized Non-negative Matrix with L0-Constraints for Selecting Characteristic Genes. ICIC (2) 2015: 612-622 - [c5]Junliang Shang, Yan Sun, Yun Fang, Shengjun Li, Jin-Xing Liu, Yuanke Zhang:
Hypergraph Supervised Search for Inferring Multiple Epistatic Interactions with Different Orders. ICIC (2) 2015: 623-633 - [c4]Jin-Xing Liu, Yong Xu, Ying-Lian Gao, Dong Wang, Chun-Hou Zheng, Junliang Shang:
Semi-supervised Feature Extraction for RNA-Seq Data Analysis. ICIC (3) 2015: 679-685 - 2012
- [c3]Chun-Hou Zheng, Jin-Xing Liu, Jian-Xun Mi, Yong Xu:
Identifying Characteristic Genes Based on Robust Principal Component Analysis. ICIC (3) 2012: 174-179 - 2007
- [c2]Jinxing Liu, Huanbin Liu, Wenhao Shen:
Stability Analysis of Particle Swarm Optimization. ICIC (2) 2007: 781-790 - 2006
- [c1]Jinxing Liu, Huanbin Liu, Wenhao Shen, Yonggen Xu, Shuangchun Yang:
A Fuzzy PID Controller for Controlling Flotation De-inking Column. ICIC (2) 2006: 90-95
Informal and Other Publications
- 2024
- [i4]Jin-Xing Liu, Wen-Yu Xi, Ling-Yun Dai, Chun-Hou Zheng, Ying-Lian Gao:
Heterogeneous network and graph attention auto-encoder for LncRNA-disease association prediction. CoRR abs/2405.02354 (2024) - [i3]Wen-Yu Xi, Juan Wang, Yu-Lin Zhang, Jin-Xing Liu, Ying-Lian Gao:
LncRNA-disease association prediction method based on heterogeneous information completion and convolutional neural network. CoRR abs/2406.03406 (2024) - 2019
- [i2]Jin-Xing Liu, Chun-Mei Feng, Xiang-Zhen Kong, Yong Xu:
Dual Graph-Laplacian PCA: A Closed-Form Solution for Bi-clustering to Find "Checkerboard" Structures on Gene Expression Data. CoRR abs/1901.06794 (2019) - [i1]Chun-Mei Feng, Yong Xu, Jin-Xing Liu, Ying-Lian Gao, Chun-Hou Zheng:
Supervised Discriminative Sparse PCA for Com-Characteristic Gene Selection and Tumor Classification on Multiview Biological Data. CoRR abs/1905.11837 (2019)
Coauthor Index
Ling-Yun Dai
aka: Lingyun Dai
aka: Lingyun Dai
[j112] [j109] [j107] [j103] [j102] [j101] [j98] [j96] [j90] [j89] [j87] [j86] [j84] [j82] [j79] [j78] [j74] [j72] [j71] [j69] [j68] [j67] [j66] [j65] [j58] [j56] [j54] [j51] [j50] [j48] [j46] [j45] [j43] [j42] [j41] [j39] [j37] [j36] [j35] [j33] [j30] [j28] [j27] [j25] [j23] [j20] [j19] [j16] [j15] [j13] [j11] [j10] [j8] [j6] [j5] [c83] [c78] [c77] [c73] [c71] [c68] [c65] [c61] [c58] [c55] [c54] [c53] [c52] [c51] [c48] [c42] [c41] [c37] [c36] [c33] [c29] [c28] [c27] [c23] [c21] [c19] [c18] [c12] [c11] [c8] [c7] [c6] [c4] [i4] [i3] [i1]
[j113] [j112] [j110] [j106] [j105] [j102] [j99] [j97] [j95] [j94] [j93] [j92] [j91] [j89] [j88] [j87] [j83] [j81] [j80] [j77] [j72] [j69] [j64] [j61] [j57] [j56] [j52] [j50] [j44] [j43] [j38] [j34] [j32] [j30] [j24] [j23] [j18] [j14] [j13] [j10] [j9] [j8] [j7] [c84] [c82] [c80] [c78] [c76] [c75] [c72] [c70] [c69] [c64] [c63] [c62] [c61] [c60] [c59] [c57] [c56] [c51] [c46] [c45] [c38] [c36] [c33] [c31] [c30] [c26] [c25] [c23] [c20] [c16] [c15] [c14] [c13] [c12] [c5] [c4]
[j108] [j105] [j98] [j93] [j92] [j90] [j89] [j83] [j81] [j79] [j78] [j77] [j75] [j74] [j73] [j71] [j67] [j64] [j63] [j62] [j55] [j48] [j45] [j40] [j36] [j30] [j28] [j26] [j25] [j22] [j21] [j20] [j17] [c82] [c78] [c75] [c72] [c64] [c63] [c61] [c60] [c59] [c56] [c50] [c49] [c47] [c43] [c36] [c32] [c27] [c21] [i3]
[j109] [j107] [j105] [j103] [j100] [j96] [j92] [j87] [j86] [j85] [j84] [j82] [j81] [j76] [j74] [j73] [j72] [j68] [j67] [j66] [j65] [j64] [j63] [j54] [j47] [j43] [j40] [j38] [j36] [j28] [j25] [j22] [j18] [j17] [j16] [j15] [j14] [j13] [j12] [j10] [j9] [j8] [j6] [j5] [j4] [j3] [j2] [j1] [c83] [c79] [c78] [c67] [c65] [c60] [c55] [c51] [c48] [c42] [c31] [c30] [c29] [c27] [c26] [c24] [c23] [c22] [c20] [c18] [c13] [c12] [c11] [c8] [c4] [c3] [i4] [i1]
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-18 21:46 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
