Cui-Na Jiao

According to our database, Cui-Na Jiao authored at least 14 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Multi-Kernel Graph Attention Deep Autoencoder for MiRNA-Disease Association Prediction.

Cui-Na Jiao, Feng Zhou, Bao-Min Liu, Chun-Hou Zheng, Jin-Xing Liu, Ying-Lian Gao

IEEE J. Biomed. Health Informatics, February, 2024

2023

Predicting miRNA-Disease Associations Through Deep Autoencoder With Multiple Kernel Learning.

Feng Zhou, Meng-Meng Yin, Cui-Na Jiao, Jing-Xiu Zhao, Chun-Hou Zheng, Jin-Xing Liu

IEEE Trans. Neural Networks Learn. Syst., September, 2023

Spatial Domain Identification Based on Graph Attention Denoising Auto-encoder.

Yue Gao, Dai-Jun Zhang, Cui-Na Jiao, Ying-Lian Gao, Jin-Xing Liu

Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023

LANCMDA: Predicting MiRNA-Disease Associations via LightGBM with Attributed Network Construction.

Xu-Ran Dou, Wen-Yu Xi, Tian-Ru Wu, Cui-Na Jiao, Jin-Xing Liu, Ying-Lian Gao

Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023

2022

Visualization and Analysis of Single Cell RNA-Seq Data by Maximizing Correntropy Based Non-Negative Low Rank Representation.

Cui-Na Jiao, Jin-Xing Liu, Juan Wang, Junliang Shang, Chun-Hou Zheng

IEEE J. Biomed. Health Informatics, 2022

Kernel risk-sensitive mean p-power loss based hyper-graph regularized robust extreme learning machine and its semi-supervised extension for sample classification.

Zhen-Xin Niu, Cui-Na Jiao, Liang-Rui Ren, Rong Zhu, Juan Wang, Jin-Xing Liu

Appl. Intell., 2022

Diagnosing Alzheimer's Disease with Bi-multitask Regularized Sparse Canonical Correlation Analysis and Logistic Regression.

Tian-Ru Wu, Cui-Na Jiao, Xinchun Cui, Jin-Xing Liu

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Probability Connectivity-Based Multimodality Regression Analysis for Associating Disease-Specific Multimodal Brain Imaging Phenotypes with Genetic Risk Factors.

Cui-Na Jiao, Chun-Hou Zheng, Jin-Xing Liu, Feng Li

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021

Bipartite graph-based collaborative matrix factorization method for predicting miRNA-disease associations.

Feng Zhou, Meng-Meng Yin, Cui-Na Jiao, Zhen Cui, Jing-Xiu Zhao, Jin-Xing Liu

BMC Bioinform., 2021

Sparse Hyper-graph Non-negative Matrix Factorization by Maximizing Correntropy.

Cui-Na Jiao, Jin-Xing Liu, Ying-Lian Gao, Xiang-Zhen Kong, Chun-Hou Zheng, Xianzi Yu

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020

Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification.

Cui-Na Jiao, Ying-Lian Gao, Na Yu, Jin-Xing Liu, Lianyong Qi

IEEE J. Biomed. Health Informatics, 2020

MCCMF: collaborative matrix factorization based on matrix completion for predicting miRNA-disease associations.

Tian-Ru Wu, Meng-Meng Yin, Cui-Na Jiao, Ying-Lian Gao, Xiang-Zhen Kong, Jin-Xing Liu

BMC Bioinform., 2020

Locally Manifold Non-negative Matrix Factorization Based on Centroid for scRNA-seq Data Analysis.

Chuan-Yuan Wang, Ying-Lian Gao, Cui-Na Jiao, Jin-Xing Liu, Chunhou Zheng, Xiang-Zhen Kong

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019

Hyper-graph Robust Non-negative Matrix Factorization Method for Cancer Sample Clustering and Feature Selection.

Cui-Na Jiao, Tian-Ru Wu, Jin-Xing Liu, Xiang-Zhen Kong

Proceedings of the Recent Advances in Data Science, 2019