A Machine-Learning Tool Concurrently Models Single Omics and Phenome Data for Functional Subtyping and Personalized Cancer Medicine

One of the major challenges in defining clinically-relevant and less heterogeneous tumor subtypes is assigning biological and/or clinical interpretations to etiological (intrinsic) subtypes. Conventional clustering/subtyping approaches often fail to define such subtypes, as they involve several disc...

Full description

Bibliographic Details
Main Authors: Gift Nyamundanda, Katherine Eason, Justin Guinney, Christopher J. Lord, Anguraj Sadanandam
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Cancers
Subjects:
Online Access:https://www.mdpi.com/2072-6694/12/10/2811