Biomarker Identification through Multiomics Data Analysis of Prostate Cancer Prognostication Using a Deep Learning Model and Similarity Network Fusion

Biomarker Identification through Multiomics Data Analysis of Prostate Cancer Prognostication Using a Deep Learning Model and Similarity Network Fusion

This study is to identify potential multiomics biomarkers for the early detection of the prognostic recurrence of PC patients. A total of 494 prostate adenocarcinoma (PRAD) patients (60-recurrent included) from the Cancer Genome Atlas (TCGA) portal were analyzed using the autoencoder model and simil...

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Bibliographic Details
Main Authors: Tzu-Hao Wang, Cheng-Yang Lee, Tzong-Yi Lee, Hsien-Da Huang, Justin Bo-Kai Hsu, Tzu-Hao Chang
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Cancers
Subjects:
prostate cancer
multiomics
autoencoder
deep learning
similarity network fusion
machine learning
Online Access:https://www.mdpi.com/2072-6694/13/11/2528

Internet

https://www.mdpi.com/2072-6694/13/11/2528

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