Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice

International initiatives such as the Molecular Taxonomy of Breast Cancer International Consortium are collecting multiple data sets at different genome-scales with the aim to identify novel cancer bio-markers and predict patient survival. To analyze such data, several machine learning, bioinformati...

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Detalles Bibliográficos
Autores principales: Simidjievski, Nikola, Bodnar, Cristian, Tariq, Ifrah, Scherer, Paul, Andres Terre, Helena, Shams, Zohreh, Jamnik, Mateja, Liò, Pietro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6917668/
https://www.ncbi.nlm.nih.gov/pubmed/31921281
http://dx.doi.org/10.3389/fgene.2019.01205

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6917668/
https://www.ncbi.nlm.nih.gov/pubmed/31921281
http://dx.doi.org/10.3389/fgene.2019.01205

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