The goal of this proposal is to establish an authoritative public database, the Comparative Toxicogenomics Database (CTD;http://ctd.mdibl.org), that promotes understanding about the effects of environmental chemicals on human health. The etiology of most chronic diseases involves interactions between environmental and genetic factors. Although more than 85,000 chemicals are used in commerce today, the complex molecular mechanisms underlying the actions of most of these chemicals and their effects on human health are poorly understood. In CTD we will present scientifically reviewed information on environmental chemicals, significant genes, and their interactions in vertebrates and invertebrates.
The specific aims of this proposal are to: 1) curate and integrate chemical-gene interactions from published literature and high-throughput experimental data (e.g., microarrays);2) curate cross-species toxicologically important genes and their proteins;and 3) transform the CTD prototype into a robust, production-quality database ready for increased public use and more sophisticated data search and analysis capabilities. CTD will be the first database to focus its curation on chemical-gene interactions and genes of toxicological significance in diverse species to elucidate structure-function correlations. These data will be key to building network models of chemical actions and providing important insights into differences in susceptibility to environmentally-induced toxicity and disease. Insights from CTD will also have important implications for toxicity prediction and environmental regulation. We are developing the publicly available Comparative Toxicogenomics Database (CTD) to promote understanding about the effects of environmental chemicals on human health. CTD will provide information on significant chemicals, genes, and their interactions in vertebrates and invertebrates. These data will provide important insights into the mechanisms of chemical actions and the genetic basis of differential toxicity among organisms and individuals, and will also have important implications for toxicity prediction and environmental regulation.
|Davis, Allan Peter; Grondin, Cynthia J; Johnson, Robin J et al. (2017) The Comparative Toxicogenomics Database: update 2017. Nucleic Acids Res 45:D972-D978|
|Mattingly, Carolyn J; Boyles, Rebecca; Lawler, Cindy P et al. (2016) Laying a Community-Based Foundation for Data-Driven Semantic Standards in Environmental Health Sciences. Environ Health Perspect 124:1136-40|
|Li, Jiao; Sun, Yueping; Johnson, Robin J et al. (2016) BioCreative V CDR task corpus: a resource for chemical disease relation extraction. Database (Oxford) 2016:|
|Grondin, Cynthia J; Davis, Allan Peter; Wiegers, Thomas C et al. (2016) Advancing Exposure Science through Chemical Data Curation and Integration in the Comparative Toxicogenomics Database. Environ Health Perspect 124:1592-1599|
|Wei, Chih-Hsuan; Peng, Yifan; Leaman, Robert et al. (2016) Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task. Database (Oxford) 2016:|
|Davis, Allan Peter; Wiegers, Thomas C; King, Benjamin L et al. (2016) Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database. PLoS One 11:e0155530|
|Davis, Allan Peter; Grondin, Cynthia J; Lennon-Hopkins, Kelley et al. (2015) The Comparative Toxicogenomics Database's 10th year anniversary: update 2015. Nucleic Acids Res 43:D914-20|
|Comeau, Donald C; Batista-Navarro, Riza Theresa; Dai, Hong-Jie et al. (2014) BioC interoperability track overview. Database (Oxford) 2014:|
|Wiegers, Thomas C; Davis, Allan Peter; Mattingly, Carolyn J (2014) Web services-based text-mining demonstrates broad impacts for interoperability and process simplification. Database (Oxford) 2014:|
|Davis, Allan Peter; Wiegers, Thomas C; Johnson, Robin J et al. (2013) Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the comparative toxicogenomics database. PLoS One 8:e58201|
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