Deep learning-based ovarian cancer subtypes identification using multi-omics data

BACKGROUND: Identifying molecular subtypes of ovarian cancer is important. Compared to identify subtypes using single omics data, the multi-omics data analysis can utilize more information. Autoencoder has been widely used to construct lower dimensional representation for multi-omics feature integra...

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Detalles Bibliográficos
Autores principales: Guo, Long-Yi, Wu, Ai-Hua, Wang, Yong-xia, Zhang, Li-ping, Chai, Hua, Liang, Xue-Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7447574/
https://www.ncbi.nlm.nih.gov/pubmed/32863885
http://dx.doi.org/10.1186/s13040-020-00222-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7447574/
https://www.ncbi.nlm.nih.gov/pubmed/32863885
http://dx.doi.org/10.1186/s13040-020-00222-x

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