Nov 30, 2015

A Bayesian network approach for modeling mixed features in TCGA ovarian cancer data

BioRxiv : the Preprint Server for Biology
Qingyang Zhang, Ji-Ping Wang

Abstract

We propose an integrative framework to select important genetic and epigenetic features related to ovarian cancer and to quantify the causal relationships among these features using a logistic Bayesian network model based on The Cancer Genome Atlas data. The constructed Bayesian network has identified four gene clusters of distinct cellular functions, 13 driver genes, as well as some new biological pathways which may shed new light into the molecular mechanisms of ovarian cancer.

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Mentioned in this Paper

Biochemical Pathway
Genome
Genes
Study of Epigenetics
Ovarian Carcinoma
Gene Clusters
Malignant Neoplasm of Ovary
deoxy(thymidylyl-cytidylyl-guanylyl-adenylic acid)
Epigenetic Process

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