Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma

Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma

Abstract Background One approach to improving the personalized treatment of cancer is to understand the cellular signaling transduction pathways that cause cancer at the level of the individual patient. In this study, we used unsupervised deep learning to learn the hierarchical structure within canc...

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Bibliographic Details
Main Authors: Jonathan D. Young, Chunhui Cai, Xinghua Lu
Format: Article
Language:English
Published: BMC 2017-10-01
Series:BMC Bioinformatics
Subjects:
Deep learning
Unsupervised learning
Cancer
Glioblastoma multiforme
Deep belief network
Gene expression
Online Access:http://link.springer.com/article/10.1186/s12859-017-1798-2

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http://link.springer.com/article/10.1186/s12859-017-1798-2

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