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Proceedings of the AMIA Symposium logoLink to Proceedings of the AMIA Symposium
. 2002:469–473.

An integrative model for in-silico clinical-genomics discovery science.

Yves A Lussier 1, Indra Nell Sarkar 1, Michael Cantor 1
PMCID: PMC2244185  PMID: 12463868

Abstract

Human Genome discovery research has set the pace for Post-Genomic Discovery Research. While post-genomic fields focused at the molecular level are intensively pursued, little effort is being deployed in the later stages of molecular medicine discovery research, such as clinical-genomics. The objective of this study is to demonstrate the relevance and significance of integrating mainstream clinical informatics decision support systems to current bioinformatics genomic discovery science. This paper is a feasibility study of an original model enabling novel "in-silico" clinical-genomic discovery science and that demonstrates its feasibility. This model is designed to mediate queries among clinical and genomic knowledge bases with relevant bioinformatic analytic tools (e.g. gene clustering). Briefly, trait-disease-gene relationships were successfully illustrated using QMR, OMIM, SNOMED-RT, GeneCluster and TreeView. The analyses were visualized as two-dimensional dendrograms of clinical observations clustered around genes. To our knowledge, this is the first study using knowledge bases of clinical decision support systems for genomic discovery. Although this study is a proof of principle, it provides a framework for the development of clinical decision-support-system driven, high-throughput clinical-genomic technologies which could potentially unveil significant high-level functions of genes.

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Barnett G. O., Cimino J. J., Hupp J. A., Hoffer E. P. DXplain. An evolving diagnostic decision-support system. JAMA. 1987 Jul 3;258(1):67–74. doi: 10.1001/jama.258.1.67. [DOI] [PubMed] [Google Scholar]
  2. Ben-Dor A., Bruhn L., Friedman N., Nachman I., Schummer M., Yakhini Z. Tissue classification with gene expression profiles. J Comput Biol. 2000;7(3-4):559–583. doi: 10.1089/106652700750050943. [DOI] [PubMed] [Google Scholar]
  3. Berner E. S., Webster G. D., Shugerman A. A., Jackson J. R., Algina J., Baker A. L., Ball E. V., Cobbs C. G., Dennis V. W., Frenkel E. P. Performance of four computer-based diagnostic systems. N Engl J Med. 1994 Jun 23;330(25):1792–1796. doi: 10.1056/NEJM199406233302506. [DOI] [PubMed] [Google Scholar]
  4. Dan Shingo, Tsunoda Tatsuhiko, Kitahara Osamu, Yanagawa Rempei, Zembutsu Hitoshi, Katagiri Toyomasa, Yamazaki Kanami, Nakamura Yusuke, Yamori Takao. An integrated database of chemosensitivity to 55 anticancer drugs and gene expression profiles of 39 human cancer cell lines. Cancer Res. 2002 Feb 15;62(4):1139–1147. [PubMed] [Google Scholar]
  5. Eisen M. B., Spellman P. T., Brown P. O., Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A. 1998 Dec 8;95(25):14863–14868. doi: 10.1073/pnas.95.25.14863. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Jimenez-Sanchez G., Childs B., Valle D. Human disease genes. Nature. 2001 Feb 15;409(6822):853–855. doi: 10.1038/35057050. [DOI] [PubMed] [Google Scholar]
  7. Khan J., Wei J. S., Ringnér M., Saal L. H., Ladanyi M., Westermann F., Berthold F., Schwab M., Antonescu C. R., Peterson C. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat Med. 2001 Jun;7(6):673–679. doi: 10.1038/89044. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Miller R. A., Pople H. E., Jr, Myers J. D. Internist-1, an experimental computer-based diagnostic consultant for general internal medicine. N Engl J Med. 1982 Aug 19;307(8):468–476. doi: 10.1056/NEJM198208193070803. [DOI] [PubMed] [Google Scholar]
  9. Miller R., Masarie F. E., Myers J. D. Quick medical reference (QMR) for diagnostic assistance. MD Comput. 1986 Sep-Oct;3(5):34–48. [PubMed] [Google Scholar]
  10. Peltonen L., McKusick V. A. Genomics and medicine. Dissecting human disease in the postgenomic era. Science. 2001 Feb 16;291(5507):1224–1229. doi: 10.1126/science.291.5507.1224. [DOI] [PubMed] [Google Scholar]
  11. Spackman K. A., Campbell K. E., Côté R. A. SNOMED RT: a reference terminology for health care. Proc AMIA Annu Fall Symp. 1997:640–644. [PMC free article] [PubMed] [Google Scholar]
  12. Venter J. C., Adams M. D., Myers E. W., Li P. W., Mural R. J., Sutton G. G., Smith H. O., Yandell M., Evans C. A., Holt R. A. The sequence of the human genome. Science. 2001 Feb 16;291(5507):1304–1351. doi: 10.1126/science.1058040. [DOI] [PubMed] [Google Scholar]
  13. Zembutsu Hitoshi, Ohnishi Yasuyuki, Tsunoda Tatsuhiko, Furukawa Yoichi, Katagiri Toyomasa, Ueyama Yoshito, Tamaoki Norikazu, Nomura Tatsuji, Kitahara Osamu, Yanagawa Rempei. Genome-wide cDNA microarray screening to correlate gene expression profiles with sensitivity of 85 human cancer xenografts to anticancer drugs. Cancer Res. 2002 Jan 15;62(2):518–527. [PubMed] [Google Scholar]

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