Abstract
The Comparative Toxicogenomics Database is a public resource that promotes understanding about the effects of environmental chemicals on human health. Currently, CTD describes over 184,000 molecular interactions for more than 5,100 chemicals and 16,300 genes/proteins. We have leveraged this dataset of chemical-gene relationships to compute similarity indices following the statistical method of the Jaccard index. These scores are used to produce lists of comparable genes ("GeneComps") or chemicals ("ChemComps") based on shared toxicogenomic profiles. GeneComps and ChemComps are now provided for every curated gene and chemical in CTD. ChemComps are particularly significant because they provide a way to group chemicals based upon their biological effects, instead of their physical or structural properties. These metrics provide a novel way to view and classify genes and chemicals and will help advance testable hypotheses about environmental chemical-genedisease networks. CTD is freely available at http://ctd.mdibl.org/
Highlights
The Comparative Toxicogenomics Database (CTD) is a public resource that promotes understanding about the effects of environmental chemicals on human health [1]
At CTD we developed a simple approach to discover analogous genes and chemicals based upon shared chemical-gene interaction profiles, which we call GeneComps and ChemComps for comparable genes and comparable chemicals, respectively
Similarity indices were computed for chemicals (ChemComps) and genes (GeneComps)
Summary
The Comparative Toxicogenomics Database (CTD) is a public resource that promotes understanding about the effects of environmental chemicals on human health [1]. CTD biocurators manually curate interactions from the scientific literature in a structured format using controlled vocabularies and ontologies for chemicals, genes, diseases, molecular interactions, and organisms [2, 3]. Finding chemicals and genes with similar interaction profiles could promote alternative methods for classifying chemicals and help identify additional members of interaction networks.
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