[논문]XPERNATO-TOX: an Integrated Toxicogenomics Knowledgebase

Woo Jung-Hoon; Kim Hyeoun-Eui; Kong Gu; Kim Ju-Han

XPERNATO-TOX: an Integrated Toxicogenomics Knowledgebase 원문보기

Genomics & informatics, v.4 no.1, 2006년, pp.40 - 44

Woo Jung-Hoon (Seoul National University Biomedical Informatics (SNUBI)) , Kim Hyeoun-Eui (Graduate Program in Health Informatics, University of Minnesota, Minneapolis) , Kong Gu (Department of Pathology, College of Medicine and Molecular Biomarker Research Center, Hanyang University) , Kim Ju-Han (Seoul National University Biomedical Informatics (SNUBI) and Human Genome Research Institute, Seoul National University College of Medicine)

Abstract ▼ AI-Helper

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.

주제어

AI 본문요약
AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

제안 방법

and human disease susceptibility. A critical part of this study is the characterization of the adverse effects at the level of the organism, the tissue, the cell, and the molecular makeup of the cell. Thus, studies in toxicology measure effects on body weight and food consumption of an organism, on individual organ weights, on microscopic histopathology of tissues, and on cell viability, necrosis, and apoptosis (Waters et al.

데이터처리

Because selecting differentially expressed genes through distinct conditions is most significant parts among the whole process, numerous algorithms have been emerged. We materi게ized SAM, cyberT, simple t-test, DEDS, ANOVA, bayesANOVA, and so on as statistical scoring modules. In most cases, selected genes are still too many to interpret individually.

참고문헌 (20)

Michael, D.W. and Jennifer, M.F. (2004). TOXICOGE NOMICS AND SYSTEMS TOXICOLOGY: AIMS AND PROSPECTS, Nature Genet. 5, 936-948

상세보기
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
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

상세보기
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

상세보기
Laura, S., Lee, E.B., and Eric B.W. (2004).Toxicogenomics in PredictiveToxicologyin DrugDevelopment. Chemistry & Biology 11,161-171

상세보기
Michael, D.W., Kenneth, O., and Raymond, W.T. (2003). Toxicogenomic approach for assessing toxicant-related disease. Mutation Research 544, 415-424

상세보기
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
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

상세보기
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
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
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

상세보기
Yang, Y.H., Xiao, Y., and Segal, M.R. (2005). Identifying differentially expressed genes from microarray experiments via statistic synthesis. Bioinformatics 21, 1084-1093

상세보기
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
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

상세보기
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
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
Benson, D.A., Boguski, M., Lipman, D.J., and Ostell, J. (1994). GenBank. Nucleic Acids Res. 22, 3441-3444

상세보기
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
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

상세보기
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

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증