This is an accompanying webpage to the paper:
Identifying network perturbation in cancer
We present a powerful computational method, called DISCERN, to identify informative topology changes in the gene network inferred from mRNA expression data. Our results show that DISCERN can identify biologically and clinically relevant network differences between disease and normal tissues, and generate testable hypotheses on the underlying mechanisms. DISCERN is a probabilistic model-based approach, which can distinguish genes that have different network connectivity with other genes between conditions. We extensively compared with methods that focus on changes in the pairwise correlations between cancer and normal tissues.