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Toxicogenomics combines transcriptome, proteome and metabolome profiling with conventional toxicology to investigate the interaction between biological molecules and toxicant or environmental stress in disease caution. Toxicogenomics faces the problems of comparison and integration across different sources of data. Cause of unusual characteristics of toxicogenomic data, researcher should be assisted by data analysis and annotation for getting meaningful information. There are already existing repositories which claim to stand for toxicogenomics database. However, those just contain limited abilities for toxicogenomic research. For supporting toxicologist who comes up against toxicogenomic data flood, now we propose novel toxicogenomics knowledgebase system, XPERANTO-TOX. XPERANTO-TOX is an integrated system for toxicogenomic data management and analysis. It is composed of three distinct but closely connected parts. Firstly, Data Storage System is for reposit many kinds of '-omics' data and conventional toxicology data. Secondly, Data Analysis System consists of analytical modules for integrated toxicogenomics data. At last, Data Annotation System is for giving extensive insight of data to researcher.

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참고문헌 (20)

  1. Michael, D.W. and Jennifer, M.F. (2004). TOXICOGE NOMICS AND SYSTEMS TOXICOLOGY: AIMS AND PROSPECTS, Nature Genet. 5, 936-948 
  2. Hamadeh, H.K., Amin, R.P., Paules, R.S.,and Afshari,C.A. (2002). An overview of toxicogenomics. Curr. Issues Mol. BioI. 4, 45-56 
  3. Aardema, M.J.and MacGregor, J.T. (2002).Toxicologyand genetic toxicology in the new era of 'toxicogenomics': impact of '-omics' technologies. Mutat. Res. 499,13-25 
  4. Mattes,W.B., Pettit, S.D., Sansone,S.A., Bushel, P.R.,and Waters, M.D. (2004). Database development in toxicog enomics: issues and efforts. Environ. Health Perspect. 112, 495-505 
  5. Laura, S., Lee, E.B., and Eric B.W. (2004).Toxicogenomics in PredictiveToxicologyin DrugDevelopment. Chemistry & Biology 11,161-171 
  6. Michael, D.W., Kenneth, O., and Raymond, W.T. (2003). Toxicogenomic approach for assessing toxicant-related disease. Mutation Research 544, 415-424 
  7. Lee, H.W., Park, Y.R., Sim, J.H., Park, R.W., Kim, W.H., and Kim, J.H. The Tissue Microarray Object Model: a data model for storage, analysis and exchange of tissue microarray experimental data, Archives of Pathology and Laboratory Medicine, accepted 
  8. Bolstad, B.M., Irizarry, R.A, Astrand, M., and Speed, T.P. (2003). A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19, 185-193 
  9. Huber, W., von Heydebreck, A., Sultmann, H., Poustka, A., and Vingron, M. (2002). Variance stabilization applied to microarray data calibration and to the quantification of differential expression. Bioinformatics 1, 1-9 
  10. Tusher, V.G., libshirani, R., and Chu, G. (2001). Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA 98, 5116-5121 
  11. Baldi, P. and Long, A.D. (2001). A Bayesian Framework for the Analysis of Microarray Expression Data: Regularized t-Test and Statistical Inferences of Gene Changes. Bioinformatics 17, 509-519 
  12. Yang, Y.H., Xiao, Y., and Segal, M.R. (2005). Identifying differentially expressed genes from microarray experiments via statistic synthesis. Bioinformatics 21, 1084-1093 
  13. Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., Paulovich, A., Pomeroy, S.L., Golub, T.R., Lander, E.S., and Mesirov, J.P. (2005) Gene set enrichment analysis: A knowledge-based approach for interpreting genome-Wide expression profiles. Proc. Natl. Acad. Sci. USA 102,15545-15550 
  14. Saidi, S.A., Holland, C.M., Kreil, D.P., MacKay, D.J., Charnock-Jones, D.S., Print, C.G., and Smith, S.K. (2004). Independent component analysis of microarray data in the study of endometrial cancer. Oncogene 23, 6677-6683 
  15. Brown, M.P., Grundy, W.N., Lin, D., Cristianini, N., Sugnet, C.W., Furey, T.S., Ares, M. and Jr Haussler, D. (2000). Knowledge-based analysis of microarraygene expression data by using support vector machines. Proc. Natl. Acad. Sci. USA 97, 262-267 
  16. Tibshirani, R., Hastie, T., Narasimhan, B., and Chu, G. (2002). Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc. Natl. Acad. Sci. USA 99, 6567-6572 
  17. Benson, D.A., Boguski, M., Lipman, D.J., and Ostell, J. (1994). GenBank. Nucleic Acids Res. 22, 3441-3444 
  18. Mattingly, C.J., Colby, G.T., Rosenstein, M.C., Forrest, J.N.Jr, Boyer, J.L. (2003). The Comparative Toxicogeno mics Database (CTD). Environmental Health Perspectives. 111, 6 
  19. Tong, W., Cao, X., Harris, S., Sun, H., Fang, H., Fuscoe, J., Harris, A., Hong, H., Xie, Q., Perkins, R., Shi, L., and Casciano, D. (2003). ArrayTrack-supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research. Environ Health Perspect.111, 1819-1826 
  20. Hamosh, A, Scott, A.F., Amberger, J.S., Bocchini, C.A, and McKusick,V.A. (2001). Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 30, 52-55 

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