PT  - JOURNAL ARTICLE
AU  - Qingyang Zhang
AU  - Ji-Ping Wang
AU  - Northwestern PSOC members
TI  - A Bayesian network approach for modeling mixed features in TCGA ovarian cancer data
AID  - 10.1101/033332
DP  - 2015 Jan 01
TA  - bioRxiv
PG  - 033332
4099  - http://biorxiv.org/content/early/2015/11/30/033332.short
4100  - http://biorxiv.org/content/early/2015/11/30/033332.full
AB  - 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.