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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Detalles Bibliográficos
Autores principales: Wang, Xichun, Branciamore, Sergio, Gogoshin, Grigoriy, Ding, Shuyu, Rodin, Andrei S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314938/
https://www.ncbi.nlm.nih.gov/pubmed/32625238
http://dx.doi.org/10.3389/fgene.2020.00648

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314938/
https://www.ncbi.nlm.nih.gov/pubmed/32625238
http://dx.doi.org/10.3389/fgene.2020.00648

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