Network Medicine in the Age of Biomedical Big Data - Sonawane, Abhijeet R.; Weiss, Scott T.; Glass, Kimberly; Sharma, Amitabh (Frontiers in Genetics, 2019)
Network medicine is an emerging area of research dealing with molecular and genetic interactions, network biomarkers of disease, and therapeutic target discovery. Research in network theory, an interdisciplinary subject, has aided the identification of meaningful biology. On the other hand, large-scale biomedical data generation provides a unique opportunity to assess the effect and impact of cellular heterogeneity and environmental perturbations on the observed phenotype. Marrying the two, network medicine with biomedical data provides a framework to build meaningful models and extract impactful results at a networks level. In this review, we survey existing network types and biomedical data sources. More importantly, we delve into ways in which the network medicine approach, aided by phenotype-specific biomedical data, can be gainfully applied. We provide three paradigms, mainly dealing with three major biological network archetypes: the protein-protein interactions, expression based, and the gene regulatory networks. For each of these paradigms, we discuss a broad overview of philosophies under which various network methods work. We also provide a few examples in each paradigm as a test case of its successful application. Finally, we delineate several opportunities and challenges in the field of network medicine. Taken together, the understanding gained from combining biomedical data with networks can be useful for knowing disease etiologies and identifying therapeutic targets, which, in turn, will lead to better preventive medicine with translational impacts on personalized healthcare.