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dc.contributor.authorChen, Meifania
dc.contributor.authorHadzic, Maja
dc.contributor.editorTharam Dillon, Daniel Rubin, William Gallagher, Amandeep Sidhu and Alexey Tsymbal
dc.identifier.citationChen, Meifania and Hadzic, Maja. 2010. Towards a Methodology for Lipoprotein Ontology, in Dillon, T. and Rubin, D. and Gallagher, W. and Sidhu, A. and Tsymbal, A. (ed), 23rd IEEE International Symposium on Computer-Based Medical Systems (CBMS 2010), Oct 12 2010, pp. 415-420. Perth, WA: IEEE.

Abnormal plasma lipoprotein levels have been found to be significantly correlated to cardiovascular disease, the leading cause of mortality and morbidity worldwide. In addition, lipoprotein dysregulation, known as dyslipidemia, is a central feature in disease states such as diabetes and hypertension, which also increases the risk to cardiovascular disease. Despite progress in lipoprotein research, a vast number of the world population suffers from dyslipidemia. One of the major challenges that researchers face is the difficulties in accessing and integrating relevant information amidst massive quantities of heterogeneous data. Ontologies target these problems by providing a semantic framework of the concepts involved in a system of related instances to support systematic querying of information, data mining, as well as form the basis for collaboration between research teams. Lipoprotein Ontology will provide the basis for the design of various applications to enable interoperability between research groups or software agents, as well as the development of tools for the diagnosis and treatment of dyslipidemia. In this paper we present a nine-step methodology for the design of Lipoprotein Ontology. This methodology can be adapted for use in the design of other domain-specific ontologies.

dc.titleTowards a Methodology for Lipoprotein Ontology
dc.typeConference Paper
dcterms.source.titleProceedings of the 23rd IEEE international symposium on computer-based medical systems (CBMS 2010)
dcterms.source.seriesProceedings of the 23rd IEEE international symposium on computer-based medical systems (CBMS 2010)
dcterms.source.conference23rd IEEE International Symposium on Computer-Based Medical Systems (CBMS 2010)
dcterms.source.conference-start-dateOct 12 2010
dcterms.source.conferencelocationPerth, Australia

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curtin.departmentDigital Ecosystems and Business Intelligence Institute (DEBII)
curtin.accessStatusOpen access

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