Gathers literature-based, manually curated associations between chemicals, gene products, phenotypes, diseases, and environmental exposures. CTD is a public resource aiming to advance the understanding about chemical exposures and human health. The database provides more than 38 million toxicogenomic relationships, as well as analysis tools. Users can explore novel connections and generate testable hypotheses about the molecular mechanisms of chemical influenced health outcomes.
A toxicogenomics database that stores gene expression profiles and traditional toxicological data derived from in vivo (rat) and in vitro (primary rat hepatocytes, primary human hepatocytes) exposure to 170 compounds at multiple dosages and time points.
Covers toxicogenomic signatures. TOXsIgN aims to archive heterogeneous data and allows users to upload lists of overexpressed/underexpressed genes from different omics experiments. It can provide data usable for cross-species and cross-technology comparisons. This database contains over 750 projects for about 900 transcriptomic studies of more than 450 compounds performed in humans, rats, mice, or drosophila.
A robust and sustainable infrastructure storing toxicogenomics data. A central data warehouse is connected to a portal with links to chemical information and molecular and phenotype data. diXa is publicly available through a user-friendly web interface. New data can be readily deposited into diXa using guidelines and templates available online. Analysis descriptions and tools for interrogating the data are available via the diXa portal.
An online web server for easy and fast visualization of smoking effects on human lung gene expression. SEGEL integrates 362 samples collected from eight public expression microarray data sets from trachea epithelial cells, large airway epithelial cells, small airway epithelial cells, and alveolar macrophage. Gene expression patterns of regular smokers and nonsmokers across these cells can be queried by gene symbols. Sex difference in response to smoking is also shown. The correlation coefficients between the gene expression and cigarette smoking consumption (the number of packs of cigarettes consumed per year) were also calculated and are shown in the web server. The current version of SEGEL contains around 42,400 annotated gene probe sets represented on the Affymetrix Human Genome U133 Plus 2.0. SEGEL will be an invaluable tool and resource for scientists interested in the effects of smoking on lung gene expression. The web server can be used to identify reliable molecular signatures for drug discovery against smoking-related diseases.
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