Systems biology approaches to interpreting genomic data

Abstract

Technological developments in genome-wide analysis have accelerated the generation of large, complex data sets characterizing human biology at the molecular level. Integration of data from different molecular levels holds great promise for gaining understanding of complex biological systems. Toxicogenomics aims to obtain a comprehensive mechanistic map of cellular processes that drive adverse outcomes. Such an integrated approach relies on combining various genome-wide profiles (DNA, RNA, protein, and metabolite) and linking these to functional endpoints to allow the identification of relevant biological pathways. Here, current strategies for generating multiomic data within the domain of toxicogenomics are highlighted, and current strategies for multiomic data integration are discussed.