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Semantic data integration for toxicogenomic laboratory experiment management systems


Mircoarray technology leads rapid screening of differential expressed gene (DEG) from various kinds of chemical exposes. Using toxicogenomics for the risk assessment, various and heterogeneous data are contributed to each step, such as genome sequence, genotype, gene expression, phenotype, disease information etc. Accordingly ontology-based knowledge representations could prove to be successful in providing the semantics for the relationships of the drugs to a wide body of target information, a standardized annotation, integration and exchange of data. To derive actual roles of the DEGs, it is essentially required to construct interactions among DEGs and to link the known information of diseases. We depict reconstruction of semantic relationship among chemical, disease, and DEGs by using omics-data and laboratory experiment raw data in constructed toxicogenomic meta database. Omics- and experimental data are able to be easily uploaded and connected to the already constructed data network. This semantic data integration may represent the chemical-specific marker and target disease by integrated toxicogenomic data including complex expression profiles and experimental raw data. We expect that this system shows early promise in helping bridge the gap between pathophysiological processes and their molecular determinants.

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Correspondence to Byeong-Chul Kang.

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Kim, HY., Lee, SM., Shin, GH. et al. Semantic data integration for toxicogenomic laboratory experiment management systems. Toxicol. Environ. Health Sci. 3, 135 (2011).

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  • Semantics
  • Data-mining
  • Microarray
  • Toxicogenomics
  • Laboratory Information Management Systems (LIMS)