Author of the publication

Regularized Non-Negative Matrix Factorization for Identifying Differentially Expressed Genes and Clustering Samples: A Survey.

, , , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 15 (3): 974-987 (2018)

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.

 

Other publications of authors with the same name

Application of Graph Regularized Non-negative Matrix Factorization in Characteristic Gene Selection., , , , and . ICIC (2), volume 9226 of Lecture Notes in Computer Science, page 601-611. Springer, (2015)MLMVFE: A Machine Learning Approach Based on Muli-view Features Extraction for Drug-Disease Associations Prediction., , , , and . ISBRA, volume 13760 of Lecture Notes in Computer Science, page 1-8. Springer, (2022)M3HOGAT: A Multi-View Multi-Modal Multi-Scale High-Order Graph Attention Network for Microbe-Disease Association Prediction., , , , and . IEEE J. Biomed. Health Informatics, 28 (10): 6259-6267 (October 2024)Identify Complex Higher-Order Associations Between Alzheimer's Disease Genes and Imaging Markers Through Improved Adaptive Sparse Multi-view Canonical Correlation Analysis., , , , and . ICIC (3), volume 14088 of Lecture Notes in Computer Science, page 324-334. Springer, (2023)DSCMF: prediction of LncRNA-disease associations based on dual sparse collaborative matrix factorization., , , , and . BMC Bioinform., 22-S (3): 241 (2021)DSNPCMF: Predicting MiRNA-Disease Associations with Collaborative Matrix Factorization Based on Double Sparse and Nearest Profile., , , , and . IDMB, volume 1099 of Communications in Computer and Information Science, page 196-208. Springer, (2019)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)MKGSAGE: A Computational Framework via Multiple Kernel Fusion on GraphSAGE for Inferring Potential Disease-Related Microbes., , , , , and . BIBM, page 648-653. IEEE, (2023)The computational prediction of drug-disease interactions using the dual-network L2,1-CMF method., , , , , and . BMC Bioinform., 20 (1): 5 (December 2019)A review of recent advances in spatially resolved transcriptomics data analysis., , , , , and . Neurocomputing, (2024)