Xiang-Zhen Kong
Orcid: 0000-0002-0805-1350
According to our database1,
Xiang-Zhen Kong authored at least 75 papers
between 2012 and 2025.
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Bibliography
2025
A Scalable and Unified Hierarchical Coarsening Hypergraph Framework for Single-Cell Multi-Omics Data Analysis.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2025
2023
A New Binary Biclustering Algorithm Based on Weight Adjacency Difference Matrix for Analyzing Gene Expression Data.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
CHLPCA: Correntropy-Based Hypergraph Regularized Sparse PCA for Single-Cell Type Identification.
Proceedings of the Bioinformatics Research and Applications - 19th International Symposium, 2023
Identify Complex Higher-Order Associations Between Alzheimer's Disease Genes and Imaging Markers Through Improved Adaptive Sparse Multi-view Canonical Correlation Analysis.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023
2022
Unsupervised Cluster Analysis and Gene Marker Extraction of scRNA-seq Data Based On Non-Negative Matrix Factorization.
IEEE J. Biomed. Health Informatics, 2022
Multi-View Random-Walk Graph Regularization Low-Rank Representation for Cancer Clustering and Differentially Expressed Gene Selection.
IEEE J. Biomed. Health Informatics, 2022
NCPLP: A Novel Approach for Predicting Microbe-Associated Diseases With Network Consistency Projection and Label Propagation.
IEEE Trans. Cybern., 2022
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
Machine learning of large-scale multimodal brain imaging data reveals neural correlates of hand preference.
NeuroImage, 2022
Tensor decomposition based on the potential low-rank and p-shrinkage generalized threshold algorithm for analyzing cancer multiomics data.
J. Bioinform. Comput. Biol., 2022
A binary biclustering algorithm based on the adjacency difference matrix for gene expression data analysis.
BMC Bioinform., 2022
2021
WGRCMF: A Weighted Graph Regularized Collaborative Matrix Factorization Method for Predicting Novel LncRNA-Disease Associations.
IEEE J. Biomed. Health Informatics, 2021
Development of navigation network revealed by resting-state and task-state functional connectivity.
NeuroImage, 2021
Kernel Risk-Sensitive Loss based Hyper-graph Regularized Robust Extreme Learning Machine and Its Semi-supervised Extension for Classification.
Knowl. Based Syst., 2021
Extreme Learning Machine Based on Double Kernel Risk-Sensitive Loss for Cancer Samples Classification.
Proceedings of the Intelligent Computing Theories and Application, 2021
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
2020
L<sub>2, 1</sub>-Extreme Learning Machine: An Efficient Robust Classifier for Tumor Classification.
Comput. Biol. Chem., 2020
MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations.
BMC Bioinform., 2020
Robust Graph Regularized Extreme Learning Machine Auto Encoder and Its Application to Single-Cell Samples Classification.
Proceedings of the Intelligent Computing Theories and Application, 2020
Tensor Robust Principal Component Analysis with Low-Rank Weight Constraints for Sample Clustering.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
Sparse Regularization Tensor Robust PCA Based on t-product and Its Application in Cancer Genomic Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
Locally Manifold Non-negative Matrix Factorization Based on Centroid for scRNA-seq Data Analysis.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
2019
A Mixed-Norm Laplacian Regularized Low-Rank Representation Method for Tumor Samples Clustering.
IEEE ACM Trans. Comput. Biol. Bioinform., 2019
Dual Graph-Laplacian PCA: A Closed-Form Solution for Bi-Clustering to Find "Checkerboard" Structures on Gene Expression Data.
IEEE Access, 2019
An Integrated Graph Regularized Non-Negative Matrix Factorization Model for Gene Co-Expression Network Analysis.
IEEE Access, 2019
DSNPCMF: Predicting MiRNA-Disease Associations with Collaborative Matrix Factorization Based on Double Sparse and Nearest Profile.
Proceedings of the Recent Advances in Data Science, 2019
Hyper-graph Robust Non-negative Matrix Factorization Method for Cancer Sample Clustering and Feature Selection.
Proceedings of the Recent Advances in Data Science, 2019
2018
2017
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.1.
Dataset, May, 2017
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.0.
Dataset, May, 2017
NeuroImage, 2017
2016
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.12.0-rc1.
Dataset, April, 2016
2015
Quantifying interindividual variability and asymmetry of face-selective regions: A probabilistic functional atlas.
NeuroImage, 2015
2012
Characterization, ecological and health risks of DDTs and HCHs in water from a large shallow Chinese lake.
Ecol. Informatics, 2012