Predicting prognostic markers for glioma using gene co-expression network analysis

Authors:
Praneeth Uppalapati;Yang Xiang;Kun Huang
Affiliations:
The Ohio State University;The Ohio State University;The Ohio State University
Venue:
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
Year:
2010

Citing 2
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Abstract

In this paper, we described our approach for selecting potential biomarkers based on gene co-expression network (GCN) analysis. We present an efficient GCN finding algorithm and applied it to search for predictive markers in glioblastoma using the TCGA data. We identified six clusters of genes as potential biomarkers, which show significant difference in survival times between patient groups separated using these genes as features. Specifically, we have identified two gene clusters which are enriched with immune genes and tumor microenvironment genes respectively. These genes represent important biological processes related to the metastasis of glioblastoma and lead to new biological insight.