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2020 – today
- 2024
[j11]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)- [j10]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) - [j9]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) - [j8]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) - [j7]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) - [c9]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
- [j6]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) - [c8]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 - [c7]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 - 2022
- [j5]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) - [j4]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) - [c6]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 - [c5]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 - [c4]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
- [j3]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) - [c3]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 - 2020
- [j2]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) - [j1]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) - [c2]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
2010 – 2019
- 2019
- [c1]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
Coauthor Index
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