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Ontological modeling at a domain interface: bridging clinical and biomolecular knowledge

Published online by Cambridge University Press:  01 September 2009

Gianluca Colombo ,
Daniele Merico ,
Zoltán Nagy ,
Flavio De Paoli ,
Marco Antoniotti  and
Giancarlo Mauri
Gianluca Colombo
Affiliation:
Department of Computer Science, Systems and Communication (DISCo), University of Milan—Bicocca, viale Sarca, 336/14, 20126 Milan, Italy; e-mail: [email protected], [email protected], [email protected], [email protected]
Daniele Merico
Affiliation:
Department of Computer Science, Systems and Communication (DISCo), University of Milan—Bicocca, viale Sarca, 336/14, 20126 Milan, Italy; e-mail: [email protected], [email protected], [email protected], [email protected] Department of Biomolecular Sciences and Biotechnologies (DSBB), University of Milan, Via Celoria, 26, 20133 Milan, Italy; e-mail: [email protected] Terrence Donnelly Centre for Cellular and Biomolecular Research (CCBR), Banting and Best Department of Medical Research, University of Toronto, 160, College Street, M5S 3E1 Toronto, Ontario, Canada
Zoltán Nagy
Affiliation:
Department of Vascular Neurology, Semmelweis University, Huvosvolgyi Street 116, 1021 Budapest, Hungary; e-mail: [email protected]
Flavio De Paoli
Affiliation:
Department of Computer Science, Systems and Communication (DISCo), University of Milan—Bicocca, viale Sarca, 336/14, 20126 Milan, Italy; e-mail: [email protected], [email protected], [email protected], [email protected]
Marco Antoniotti
Affiliation:
Department of Computer Science, Systems and Communication (DISCo), University of Milan—Bicocca, viale Sarca, 336/14, 20126 Milan, Italy; e-mail: [email protected], [email protected], [email protected], [email protected]
Giancarlo Mauri
Affiliation:
Department of Computer Science, Systems and Communication (DISCo), University of Milan—Bicocca, viale Sarca, 336/14, 20126 Milan, Italy; e-mail: [email protected], [email protected], [email protected], [email protected]
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Abstract

In this paper, we discuss the challenges posed by the NEUROWEB project, as a case study of ontological modeling at a knowledge interface between neurovascular medicine and genomics. The aim of the project is the development of a support system for association studies. We identify the notion of clinical phenotypes, that is, the pathological condition of a patient, as the central construct of the knowledge model. Clinical phenotypes are assessed through the diagnostic activity, performed by clinical experts operating within communities of practice; the different communities operate according to specific procedures, but they also conform to the minimal requirements of international guidelines, displayed by the adoption of a common standard for the patient classification. We develop a central model for the clinical phenotypes, able to reconcile the different methodologies into a common classificatory system. To bridge neurovascular medicine and genomics, we identify the general theory of biological function as the common ground between the two disciplines; therefore, we decompose the clinical phenotypes into elementary phenotypes with a homogeneous physiological background, and we connect them to the biological processes, acting as the elementary units of the genomic world.

Type
Original Article
Information
The Knowledge Engineering Review , Volume 24 , Special Issue 3: Software and system engineering – part 2 , September 2009 , pp. 205 - 224
Copyright
Copyright © Cambridge University Press 2009

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References

Adams, H. P. Jr., Bendixen, B. H., Kappelle, L. J., Biller, J., Love, B. B., Gordon, D. L., Marsh, E. E. 3rd. 1993. Classification of subtype of acute ischemic stroke, definition for use in a multicenter clinical trial, TOAST. Trial of Org 10172 in acute stroke treatment. Stroke 24, 35–41.CrossRefGoogle Scholar
Ay, H., Furie, K. L., Singhal, A., Smith, W. S., Sorensen, A. G., Koroshetz, W. J. 2005. An evidence-based causative classification system for acute ischemic stroke. Annals of Neurology 58, 688–697.CrossRefGoogle ScholarPubMed
Baader, F., Calvanese, D., McGuinness, D. L. et al. 2003. The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press.Google Scholar
Bandini, S., Colombo, E., Colombo, G., Sartori, F., Simone, C. 2003. The role of knowledge artifacts in innovation management: the case of a chemical compound designer CoP. International Conference on Communities and Technologies, Kluwer Academic Publishers, 327–345.Google Scholar
Bard, J. B., Rhee, L., Seung, Y. 2004. Ontology in biology: design, application and future challenges. Nature Reviews Genetics 5(3), 213–222.CrossRefGoogle ScholarPubMed
Benassi, R., Beneventano, D., Bergamaschi, S., Guerra, F., Vincini, M. 2004. Synthesizing an integrated ontology with MOMIS. International Conference on Knowledge Engineering and Decision Support (ICKEDS), Porto, Portugal, 21–23 July 2004.Google Scholar
Benerecetti, M., Bouquet, P., Ghidini, C. 2000. Contextual reasoning distilled. Journal of Theoretical and Artificial Intelligence (JETAI) 12, 279–305.CrossRefGoogle Scholar
Bergamaschi, S., Guerra, F., Orsini, M., Sartori, C. 2007. Extracting relevant attribute values for improved search. IEEE Internet Computing 11(5), 26–35.CrossRefGoogle Scholar
Bodenreider, O., Smith, B., Kumar, A., Burgun, A. 2007. Investigating subsumption in DL-based terminologies: a case study in SNOMED CT. Artificial Intelligence in Medicine 39(3), 183–195.CrossRefGoogle Scholar
Boland, J., Tenkasi, R. V. 1995. Perspective making and perspective taking in communities of knowing. Organizational Science 6(4), 350–372.CrossRefGoogle Scholar
Bouquet, P., Don, V., Serafini, A. 2002. ConTeXtualized local ontology specification via ctxml. In Proceedings of AAAI workshop on Meaning Negotiation, Edmonton, Alberta, Canada.Google Scholar
Bowker, G. C., Turner, W., Star, S. L., Gasser, L. 1997. Social Science, Technical Systems, and Cooperative Work: Beyond the Great Divide. Lawrence Erlbaum Associates.Google Scholar
Brown, J. S., Duguid, P. 1991. Organizational learning and community of practice: toward a unified view of working. Organization Science 2(1), 40–57.CrossRefGoogle Scholar
Chandrasekaran, B., Josephson, J. R., Benjamins, V. R. 1999. What are ontologies, and why do we need them? Intelligent systems and their applications. IEEE 14(1), 20–26.Google Scholar
Colombo, G., Mosca, A., Sartori, F. 2007. Towards the design of intelligent CAD systems: an ontological approach. International Journal on Advanced Engineering Informatics – Special Issue on Ontology and Epistemology of Systems and Software Engineering 22(2), 153–168.Google Scholar
Davenport, T., Prusack, L. 1998. Working Knowledge: How Organizations Manage What They Know. HBS Press.Google Scholar
Douglas, K. 2005. PostgreSQL (2nd edn). Sams.Google Scholar
Feyerabend, P. 1975. Against Method: Outline of an Anarchistic Theory of Knowledge. Verso.Google Scholar
Goldstein, L. B., Jones, M. R., Matchar, D. B. et al. 2001. Improving the reliability of stroke subgroup classification using the trial of ORG 10172 in acute stroke treatment (TOAST) criteria. Stroke 32, 1091–1097.CrossRefGoogle ScholarPubMed
Gomez-Perez, A., Corcho-Garcia, O., Fernandez-Lopez, M. 2003. Ontological Engineering. Springer-Verlag.Google Scholar
Gruber, T. R. 1995. Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human–Computer Studies 43(4–5), 907–928.CrossRefGoogle Scholar
Guarino, N. 1995. Formal ontology, conceptual analysis and knowledge representation. International Journal of Human–Computer Studies 43(5–6), 625–640.CrossRefGoogle Scholar
Guarino, N. 1998. Formal ontology in information systems. In Proceedings of FOIS’98, Trento, Italy. IOS Press, 3–15.Google Scholar
Guida, G., Berini, G. 2000. Ingegneria della Conoscenza: Strumenti per Innovare e per Competere. EGEA.Google Scholar
Guizzardi, G. 2007. On ontology, ontologies, conceptualizations, modeling languages, and (meta)models. In Frontiers in Artificial Intelligence and Applications, Databases and Information Systems IV, Vasilecas, O., Eder, J. & Caplinskas, A. (eds). IOS Press, 18–39.Google Scholar
Hildreth, P., Kimble, C., Wright, P. 2000. Communities of practice in the distributed international environment. Journal of Knowledge Management 4(1), 27–37.CrossRefGoogle Scholar
Holsapple, C. W., Joshi, K. D. 2001. Organizational knowledge resources. Decision Support Systems 31(1), 39–54.CrossRefGoogle Scholar
Horrocks, I., Patel-Schneider, P. 2003. Reducing OWL entailment to description logic satisfiability. In Proceedings of the 2nd International Semantic Web Conference (ISWC).CrossRefGoogle Scholar
Horrocks, I., Sattler, U., Tobies, S. 1999. Practical Reasoning for Expressive Description Logics. Springer-Verlag.CrossRefGoogle Scholar
Johnson-Laird, P. N. 1983. Mental Models: Towards a Cognitive Science of Language, Inference, and Consciousness. Harvard University Press.Google Scholar
Kitamura, Y., Mizoguchi, R. 2003. Ontology-based description of functional design knowledge and its use in a functional way server. International Journal of Expert System with Application 24(2), 153–166.CrossRefGoogle Scholar
Kuhn, T. 1970. The Structure of Scientific Revolutions. University of Chicago Press.Google Scholar
Lakatos, I. 1978. The Methodology of Scientific Research Programmes, Philosophical Papers, volume 1, Cambridge University Press.CrossRefGoogle Scholar
Laudan, L. 1977. Progress and its Problems: Toward a Theory of Scientific Growth. University of California at Berkeley.Google Scholar
Lee, L. J. et al. 2000. Impact on stroke subtype diagnosis of early diffusion-weighted magnetic resonance imaging and magnetic resonance angiography. Stroke 31, 1081–1089.CrossRefGoogle ScholarPubMed
Lenzerini, M. 2002. Data Integration: A Theoretical Perspective. ACM PODS, 233–246.Google Scholar
Lueg, C. 2002. Knowledge management and information technology: relationship and perspective. Upgrade—Knowledge Management and Information Technology. Introduction to the special issue, III(1).Google Scholar
Miller, R. A. 1994. Medical diagnostic decision support systems. Past, present, and future: a threaded bibliography and brief commentary. Journal of American Medical Informatics Association 1(1), 8–27.CrossRefGoogle ScholarPubMed
Mork, P., Brinkley, J. F., Rosse, C. 2003. OQAFMA Querying Agent for the Foundational Model of Anatomy: a prototype for providing flexible and efficient access to large semantic networks. Journal of Biomedical Informatics (36), 501–517.CrossRefGoogle ScholarPubMed
Nonaka, H., Takeuchi, I. 1995. The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press.CrossRefGoogle Scholar
OBO. 2007. Open Biomedical Ontologies. http://obo.sourceforge.net/ (November 2007).Google Scholar
Preece, A., Sleeman, D. H., Flett, A. N. et al. 2001. Better knowledge management through knowledge engineering. IEEE Intelligent Systems 16(1), 36–43.CrossRefGoogle Scholar
Sattler, U. 2000. Description logics for the representation of aggregated objects. In Proceedings of the 14th European Conference on Artificial Intelligence, IOS Press.Google Scholar
Sicilia, J. J., Sicilia, M. A., Sánchez-Alonso, S. et al. 2009. Knowledge representation issues in ontology-based clinical knowledge management systems. International Journal of Technology Management 47, 191–206.CrossRefGoogle Scholar
Simons, P. 1987. Parts: A Study in Ontology. Oxford University Press.Google Scholar
Smith, B. 2004. Beyond concepts: ontology as reality representation. In Proceedings of FOIS’04.Google Scholar
Smith, B., Kusnierczyk, W., Schober, D., Ceusters, W. 2006. Towards a reference terminology for ontology research and development in the biomedical domain. In Proceedings of KR-MED.Google Scholar
Protégé version 3.0 2004. Standford University. http://protege.stanford.edu/ (13 October 2004).Google Scholar
Stenson, P. D., Ball, E. V., Mort, M., Phillips, A. D., Shiel, J. A., Thomas, N. S., Abeysinghe, S., Krawczak, M., Cooper, D. N. 2003. Human Gene Mutation Database (HGMD). Human Mutation 21(6), 577–581.CrossRefGoogle ScholarPubMed
Studer, R., Benjamins, R. V., Fensel, D. 1998. Knowledge engineering: principles and methods. Data Knowledge Engineering Journal 25(1–2), 161–167.CrossRefGoogle Scholar
The Gene Ontology Consortium. http://www.geneontology.orgGoogle Scholar
The National Center for Biomedical Ontologies, http://www.bioontology.org/wiki/index.php/MainpageGoogle Scholar
Thomasson, A. L. 2004. Methods of categorization. In Proceedings of the 3rd International Conference (FOIS’04), IOS Press, 3–16.Google Scholar
Van der Vet, P. E., Mars, N. J. I. 1998. Bottom-up construction of ontologies. IEEE Transactions on Knowledge and Data Engineering 10(4), 513–526.CrossRefGoogle Scholar
Wenger, E. 1998. Community of Practice: Learning, Meaning and Identity. Cambridge University Press.CrossRefGoogle Scholar
W3C—Web Ontology Language 2004. http://www.w3.org/TR/owl-guide/ (10 February 2004).Google Scholar
Zaihrayeu, I., Sun, L., Giunchiglia, F. et al. 2007. From Web Directories to Ontologies: Natural Language Processing Challenges. In Proceedings of the 6th International Semantic Web Conference and the 2nd Asian Semantic Web Conference, Busan, Korea, 623–636.Google Scholar