We apply our algorithms to several cancer types including glioblastoma multiforme (GBM), lung adenocarcinoma, and ovarian carcinoma (OV). HotNet identifies significant subnetworks that are part of well-known cancer pathways as well as novel subnetworks. Among the most significant subnetworks identified in OV data is the Notch signaling pathway, and this result appears in the first TCGA OV publication . We also extend HotNet to identify mutated pathways associated with patient survival . In the TCGA OV data, we discover 9 subnetworks containing genes whose mutations are associated with survival. Genes in 4 of these subnetworks overlap pathways known to be associated to survival, including focal adhesion and cell adhesion pathways. In GBM and lung Dendrix finds significant sets of genes that are mutated in large subsets of patients and whose mutations are approximately exclusive, including genes in well known cancer pathways (e.g., Rb1 and p53 pathways).