New Analysis Framework Incorporating Mixed Mutual Information and Scalable Bayesian Networks for Multimodal High Dimensional Genomic and Epigenomic Cancer Data

New Analysis Framework Incorporating Mixed Mutual Information and Scalable Bayesian Networks for Multimodal High Dimensional Genomic and Epigenomic Cancer Data

We propose a novel two-stage analysis strategy to discover candidate genes associated with the particular cancer outcomes in large multimodal genomic cancers databases, such as The Cancer Genome Atlas (TCGA). During the first stage, we use mixed mutual information to perform variable selection; duri...

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Bibliographic Details
Main Authors: Xichun Wang, Sergio Branciamore, Grigoriy Gogoshin, Shuyu Ding, Andrei S. Rodin
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-06-01
Series:Frontiers in Genetics
Subjects:
The Cancer Genome Atlas
Bayesian networks
multimodal big data
variable selection
mixed mutual information
methylation
Online Access:https://www.frontiersin.org/article/10.3389/fgene.2020.00648/full

Internet

https://www.frontiersin.org/article/10.3389/fgene.2020.00648/full

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