Network and pathway analysis of toxicogenomics data

With the aim of elucidating toxicological mechanisms, building predictive models and improving diagnostics and studying of the molecular effects of chemical, biological and physical agents in biological systems is known as toxicogenomics.Major proportion of toxicogenomics data generated at the transcriptome level, including RNAseq as well as microarrays, and large quantities of drug-treatment data are publicly available through databases and repositories. The identification of differentially expressed genes (DEGs) from case-control studies or drug treatment time series studies, bioinformatics methods have emerged that infer gene expression data at the molecular network and pathway level in order to reveal mechanistic information. Approaches that highlight the integrate gene expression data with molecular interaction networks in order to derive network modules related to drug toxicity. The two main parts of the approach, i.e., the construction of a suitable molecular interaction network as well as the conduction of network propagation of the experimental data through the interaction network.