Precision cancer medicine promises to tailor clinical decisions to patients using genomic information. Indeed, successes of drugs targeting genetic alterations in tumors, such as imatinib that targets BCR–ABL in chronic myelogenous leukemia, have demonstrated the power of this approach. However, biological systems are complex, and patients may differ not only by the specific genetic alterations in their tumor, but also by more subtle interactions among such alterations. Systems biology and more specifically, network analysis, provides a framework for advancing precision medicine beyond clinical actionability of individual mutations. Here we discuss applications of network analysis to study tumor biology, early methods for N-of-1 tumor genome analysis, and the path for such tools to the clinic. Display omitted •Networks provide a platform for inference from 'omic data.•Many network-based methods have been developed around cancer 'omic data analysis.•Most tumor network analyses rely on cohorts, but some N-of-1 methods exist.•Many challenges remain for applying network-based analysis in clinical settings.