Robust feature learning using contractive autoencoders for multi-omics clustering in cancer subtyping

•We propose a novel multi-omics framework using contractive autoencoder for robust feature extraction.•Cox regression integrates survival analysis to identify key survival-related features for clustering.•Experimental results demonstrate the superior performance of our method in multi-omics data ana...

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Vydané v:	Methods (San Diego, Calif.) Ročník 233; s. 52 - 60
Hlavní autori:	Guo, Mengke, Ye, Xiucai, Huang, Dong, Sakurai, Tetsuya
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Inc 01.01.2025
Predmet:	Algorithms Cancer subtyping Cluster Analysis Contractive autoencoder Genomics - methods Humans Multi-omics clustering Multiomics Neoplasms - classification Neoplasms - genetics Neoplasms - metabolism Proportional Hazards Models Contractive autoencoder Cancer subtyping Multi-omics clustering
ISSN:	1046-2023, 1095-9130, 1095-9130
On-line prístup:	Získať plný text
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