"Network medicine, a new field which developed from the application of systems biology approaches to human disease, embraces the complexity of multifactorial influences on disease, which can be driven by non-linear effects and molecular and statistical interactions.The development of comprehensive and affordable Omics platforms provides the data types for network medicine, and graph theory and statistical physics provide the theoretical framework to analyze networks. While network medicine provides a fundamentally different approach to understanding disease etiology, it will also lead to key differences in how diseases are treated--with multiple molecular targets that may require manipulation in a coordinated, dynamic fashion. Much remains to be learned regarding the optimal approaches to integrate different Omics data types and to perform network analyses; this book provides an overview of the progress that has been made and the challenges that remain."--
