Computational systems toxicology: Emergence, development and application
Chen Zhang, Yun Tang, Jie Li, Qiupeng Peng, KeJia LI · Chinese Science Bulletin (Chinese Version) · 2015
With the development of systems biology, there are new opportunities for the transformation of classical toxicology. Computational systems toxicology aims at building multi-level and multi-scale predictive models to quantitatively assess chemical safety, combining toxicogenomic experimental data. Many methods have been developed for computational systems toxicology; examples are methods that employ static network analysis and prediction, dynamic network simulation and adverse outcome pathways. Although in its early stage, computational systems toxicology has been applied to the overall understanding mechanism of toxicology, allowing the discovery of new biomarkers and the comprehensive assessment of chemical safety. This review mainly focuses on related data sources, the research status, applications, challenges and perspectives.