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A novel stratification framework for predicting outcome in patients with prostate cancer

BACKGROUND: Unsupervised learning methods, such as Hierarchical Cluster Analysis, are commonly used for the analysis of genomic platform data. Unfortunately, such approaches ignore the well-documented heterogeneous composition of prostate cancer samples. Our aim is to use more sophisticated analytic...

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Detalles Bibliográficos
Autores principales:	Luca, Bogdan-Alexandru, Moulton, Vincent, Ellis, Christopher, Edwards, Dylan R., Campbell, Colin, Cooper, Rosalin A., Clark, Jeremy, Brewer, Daniel S., Cooper, Colin S.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2020
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217762/ https://www.ncbi.nlm.nih.gov/pubmed/32203215 http://dx.doi.org/10.1038/s41416-020-0799-5

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