Network Biology in Medicine and Beyond

Abstract

In the past decade, we have witnessed great advances in high-throughput genomic and proteomic profiling technologies, such as DNA microarrays, next-generation sequencing and mass spectrometry–based proteomics and metabolomics. These advances, capable of generating massive amounts of genomic, transcriptomic, proteomic, and metabolomic data, provide new opportunities to understand human diseases, identify potential biomarkers, and develop new treatments.1 This data-intensive paradigm has fundamentally transformed biomedical science and holds great promise for the betterment of human health.2 These high-throughput biotechnologies have also heightened the challenges of how to distill biological knowledge and novel insights from the sea of data. New computational approaches and statistical models are needed to effectively model and better interpret these high-dimensional, multiplatform data.1 Reductionism has led to tremendous success in molecular biology: we can now zoom in to study each individual genes or proteins, being able to study their composition and aberrations at the resolution of single nucleotide or amino acid and inquire their structural and chemical properties. However, genes and proteins in cells do not work in isolation: they communicate and coordinate with each other to carry out various biological functions. Systems approaches have become an important and promising alternative to unravel the mechanisms that orchestrate the activities of genes and proteins in cells. Systems approaches are particularly valuable to study complex diseases like cancers and cardiovascular diseases. Unlike many Mendelian diseases, where we can often pinpoint genetic culprits in single or a few genes, causes of complex diseases are multifaceted, involving various molecular aberrations and environmental factors.3 This complexity is further amplified by the interconnected nature of the biomolecules in the cells, which propagates these aberrations or erroneous signals throughout the system, thus posing a great challenge to elucidate the true causes and underlying mechanisms. Biological networks provide a conceptual and intuitive framework …