Network Medicine in the Age of Biomedical Big Data

Abstract

Network medicine is an emerging area of research dealing with molecular and genetic interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale biomedical data generation offers 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 network 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: protein-protein interaction, expression-based, and 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. We hope this review provides a lexicon for researchers from biological sciences and network theory to come on the same page to work on research areas that require interdisciplinary expertise. Taken together, the understanding gained from combining biomedical data with networks can be useful for characterizing disease etiologies and identifying therapeutic targets, which, in turn, will lead to better preventive medicine with translational impact on personalized healthcare.

Integrative Multi-Omics Analysis in Calcific Aortic Valve Disease Reveals a Link to the Formation of Amyloid-Like Deposits

“…Nevertheless, this intuitive framework to model different components of multiple omics data illustrates one attempt to meet the promise of network medicine research [ 88 ]. The field seeks to integrate biomedical big data and uncover clinically relevant biology by identifying the pathways inside of the disease network rather than isolated components of it.…”

Integrating Genetics and Omics to Understand Chronic Obstructive Pulmonary Disease

“…The recognition that biological systems function as molecular networks has helped to crystallize thinking about combining multiple Omics data in the field of Network Medicine 2,38 . The various methods utilized to build molecular networks have been recently reviewed by members of the International Network Medicine Consortium 39 .…”

Constructing Gene Regulatory Networks using Epigenetic Data

“…19 PANDA constructs regulatory networks by integrating transcription factor motif information with protein interaction and gene co-expression data. PANDA has been widely applied a wide range of biological problems, including the study of human diseases [20][21][22] , tissues 23,24 , and cell lines [25][26][27] . While PANDA has been extremely successful, it does not explicitly incorporate epigenetic data.…”