Taking Bioinformatics to Systems Medicine

Abstract

Systems medicine promotes a range of approaches and strategies to study human health and disease at a systems level with the aim of improving the overall well-being of (healthy) individuals, and preventing, diagnosing, or curing disease. In this chapter we discuss how bioinformatics critically contributes to systems medicine. First, we explain the role of bioinformatics in the management and analysis of data. In particular we show the importance of publicly available biological and clinical repositories to support systems medicine studies. Second, we discuss how the integration and analysis of multiple types of omics data through integrative bioinformatics may facilitate the determination of more predictive and robust disease signatures, lead to a better understanding of (patho)physiological molecular mechanisms, and facilitate personalized medicine. Third, we focus on network analysis and discuss how gene networks can be constructed from omics data and how these networks can be decomposed into smaller modules. We discuss how the resulting modules can be used to generate experimentally testable hypotheses, provide insight into disease mechanisms, and lead to predictive models. Throughout, we provide several examples demonstrating how bioinformatics contributes to systems medicine and discuss future challenges in bioinformatics that need to be addressed to enable the advancement of systems medicine.

Keywords: Bioinformatics; Biological networks; Information management; Integrative bioinformatics; Multi-omics; Systems medicine; Top-down systems biology.

Fig. 1

The contribution ofbioinformatics (dark grey boxes) to systems medicine (black box). (Omics) experiments, patients, and public repositories provide a wide range of data that is used in bioinformatics and systems medicine studies

Fig. 2

Overview of network-based approaches for systems medicine (Subheading 6)