Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches - PubMed (original) (raw)

Review

Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches

Anastasis Oulas et al. Brief Bioinform. 2019.

Abstract

Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine.

Keywords: Systems Bioinformatics; computational diagnostics; computational therapeutics; drug repurposing; network analysis; precision medicine.

© The Author 2017. Published by Oxford University Press.

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Figures

Figure 1

Figure 1

Systems Bioinformatics. A schematic representation of the emergence of Systems Bioinformatics as a distinct discipline among other interrelated and interdependent disciplines. The information provided by Bioinformatics, Biology and Systems Biology is integrated in the Systems Bioinformatics framework through computational integration and network-based and other holistic approaches to tackle challenges in Systems Medicine and in particular P4 Medicine.

Figure 2

Figure 2

Network Integration. Multiscale and multisource data generated from the Human System can be represented in network form. These networks can be further analysed and, importantly, they can be integrated forming supernetworks and building a comprehensive profile of the Human System.

Figure 3

Figure 3

Network Basics. (A) The basic elements of a network are illustrated in this simple network where a circle indicates a node and a line indicates an edge. (B) Networks can be either undirected (upper panel) or directed (lower panel). (C) Hubs (red nodes – or dark grey nodes in Black & White printing) and bottlenecks (green nodes – or medium grey nodes in Black & White printing) are illustrated in this sample graph. Two example modules (green and blue areas – or shadowed areas in Black & White printing) are illustrated as subgroups of nodes and their respective edges.

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