Performance Comparison of Deep Learning Autoencoders for Cancer Subtype Detection Using Multi-Omics Data

Performance Comparison of Deep Learning Autoencoders for Cancer Subtype Detection Using Multi-Omics Data

A heterogeneous disease such as cancer is activated through multiple pathways and different perturbations. Depending upon the activated pathway(s), the survival of the patients varies significantly and shows different efficacy to various drugs. Therefore, cancer subtype detection using genomics leve...

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Bibliographic Details
Main Authors: Edian F. Franco, Pratip Rana, Aline Cruz, Víctor V. Calderón, Vasco Azevedo, Rommel T. J. Ramos, Preetam Ghosh
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Cancers
Subjects:
cancer subtype detection
multi-omics data
data integration
autoencoder
survival analysis
Online Access:https://www.mdpi.com/2072-6694/13/9/2013

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https://www.mdpi.com/2072-6694/13/9/2013

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