The structure and function of biological systems are determined by a complex network of interactions among cell components. Network medicine offers a toolset for us to systematically explore perturbations in biological networks and to understand how they can spread and affect other cellular processes. In this way, we can have mechanistic insights underlying diseases and phenotypes, evaluate gene function in the context of their molecular interactions, and identify molecular relationships among apparently distinct phenotypes. These tools have also enabled the interpretation of heterogeneity among biological samples, identification of drug targets and drug repurposing as well as biomarker discovery. As our ability to profile biological samples increases, these network-based approaches are fundamental for data integration across the genomic, transcriptomic, and proteomic sciences. Here, we review and discuss the recent advances in network medicine, exploring the different types of biological networks, several methods, and their applications.