Article

Variational autoencoders for cancer data integration: design principles and computational practice

2019-07-30

Abstract excerpt

<h4>ABSTRACT</h4> International initiatives such as the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) are collecting multiple data sets at different genome-scales with the aim to identify novel cancer bio-markers and predict patient survival. To analyse such data, several machine learning, bioinformatics and statistical methods have been applied, among them neural networks such as autoen...

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Literature Corpus work: 52704c04-f72e-5cfb-a1ae-420dbbab5122
DOI: 10.1101/719542

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