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dbZach: A comprehensive toxicogenomic information managment and knowledge discovery system. Burgoon, LD*1,3,4, Boutros, PC2,3,4, Dere, E2,3,4, Doran, S2,3,4, Pai, SS2,3,4, Aiyar, R2,3,4, Vakharia, J2,3,4, Rotman, R2,3,4, Adams, A2,3,4, Lau, B2,3,4, Patel, R2,3,4, Zacharewski, TR2,3,4. 1Dept of Pharmacology & Toxicology, 2Dept of Biochemistry & Molecular Biology, 3Center for Integrative Toxicology, and 4National Food Safety & Toxicology Center, Michigan State University, East Lansing, MI 48824. dbZach (http://dbzach.fst.msu.edu), a Minimum Information About a Microarray Experiment -Toxicology (MIAME/Tox) supportive toxicogenomic relational database, uses Java-based data mining and visualization tools to facilitate toxicogenomic data quality assurance and control, and knowledge discovery. Currently, dbZach contains subsystems for the management of in-life and in vitro sample annotation, pathology, and toxicity data, cDNA clones and annotation, microarray images, raw and normalized data, and quantitative real-time PCR results. Knowledge from cDNA and Affymetrix microarray experiments are anchored to data from complementary studies (e.g. pathology, clinical chemistry) to facilitate mechanistic understanding of toxicological responses. By managing multi-species data, and leveraging orthologous mappings through the integration of data from Ensembl, direct cross-species comparisons are made. dbZach also streamlines microarray data submittal to repositories (e.g., Gene Expression Omnibus and ArrayExpress) by formatting data in Microarray Gene Expression (MAGE) Markup Language files (MAGE-ML). Future developments for dbZach include management of biological pathway information, and integrated quality control tools. The dbZach System will be made source-available for local implementation as an independently-operated laboratory information management and knowledge discovery system. Supported by NIH grants *T32 ES07255 ES 04911-12, ES 011271 and ES 011777. |
