( en | de | ru )

 

Disambiguation of "Jiao, Cui-Na"

Author of the publication

copydeleteadd this publication to your clipboard
Bipartite graph-based collaborative matrix factorization method for predicting miRNA-disease associations.

, , , , , and . BMC Bioinform., 22 (1): 573 (2021)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Li Jiao

Yang Jiao

Yuanyong Jiao

Xiangyang Jiao

Na Na r

 

Other publications of authors with the same name

THSLRR: A Low-Rank Subspace Clustering Method Based on Tired Random Walk Similarity and Hypergraph Regularization Constraints., , , , , and . SDSC, volume 1725 of Communications in Computer and Information Science, page 80-93. Springer, (2022)Deep Hyper-Laplacian Regularized Self-representation Learning Based Structured Association Analysis for Brain Imaging Genetics., , , , , and . ISBRA (1), volume 14954 of Lecture Notes in Computer Science, page 418-426. Springer, (2024)Locally Manifold Non-negative Matrix Factorization Based on Centroid for scRNA-seq Data Analysis., , , , , and . BIBM, page 121-125. IEEE, (2020)Hyper-Graph Regularized Constrained NMF for Selecting Differentially Expressed Genes and Tumor Classification., , , , and . IEEE J. Biomed. Health Informatics, 24 (10): 3002-3011 (2020)Visualization and Analysis of Single Cell RNA-Seq Data by Maximizing Correntropy Based Non-Negative Low Rank Representation., , , , and . IEEE J. Biomed. Health Informatics, 26 (4): 1872-1882 (2022)Diagnosing Alzheimer's Disease with Bi-multitask Regularized Sparse Canonical Correlation Analysis and Logistic Regression., , , and . BIBM, page 1268-1273. IEEE, (2022)Hyper-graph Robust Non-negative Matrix Factorization Method for Cancer Sample Clustering and Feature Selection., , , and . IDMB, volume 1099 of Communications in Computer and Information Science, page 112-125. Springer, (2019)FSCME: A Feature Selection Method Combining Copula Correlation and Maximal Information Coefficient by Entropy Weights., , , , , and . IEEE J. Biomed. Health Informatics, 28 (9): 5638-5648 (September 2024)Sparse Hyper-graph Non-negative Matrix Factorization by Maximizing Correntropy., , , , , and . BIBM, page 418-423. IEEE, (2021)Spatial Domain Identification Based on Graph Attention Denoising Auto-encoder., , , , and . ICIC (3), volume 14088 of Lecture Notes in Computer Science, page 359-367. Springer, (2023)