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dc.contributor.authorChen, Meifania
dc.contributor.authorHadzic, Maja
dc.contributor.editorHamid R Arabnia and Quoc-Nam Tran
dc.date.accessioned2017-01-30T10:46:42Z
dc.date.available2017-01-30T10:46:42Z
dc.date.created2012-03-23T01:19:37Z
dc.date.issued2011
dc.identifier.citationChen, Meifania and Hadzic, Maja. 2011. A framework for lipoprotein ontology, in H.R.R. Arabnia and Q.N. Tran (ed), Software tools and algorithms for biological systems, pp. 547-553. Heidelberg: Springer.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/5512
dc.identifier.doi10.1007/978-1-4419-7046-6_55
dc.description.abstract

Clinical and epidemiological studies have established a significant correlation between abnormal plasma lipoprotein levels and cardiovascular disease, which remains the leading cause of mortality in the world today. In addition, lipoprotein dysregulation, known as dyslipidemia, is a central feature in disease states, such as diabetes and hypertension, which increases the risk of cardiovascular disease. While a corpus of literature exists on different areas of lipoprotein research, one of the major challenges that researchers face is the difficulties in accessing and integrating relevant information amidst massive quantities of heterogeneous data. Semantic web technologies, specifically ontologies, target these problems by providing an organizational framework of the concepts involved in a system of related instances to support systematic querying of information. In this paper, we identify issues within the lipoprotein research domain and present a preliminary framework for Lipoprotein Ontology, which consists of five specific areas of lipoprotein research: Classification, Metabolism, Pathophysiology, Etiology, and Treatment. By integrating specific aspects of lipoprotein research, 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.

dc.publisherSpringer
dc.subjectEtiology
dc.subjectClassification
dc.subjectPathophysiology
dc.subjectOntology
dc.subjectLipoproteins
dc.subjectLipoprotein ontology
dc.subjectTreatment
dc.subjectMetabolism
dc.titleA framework for lipoprotein ontology
dc.typeBook Chapter
dcterms.source.startPage547
dcterms.source.endPage553
dcterms.source.titleSoftware tools and algorithms for biological systems: advances in experimental medicine and biology
dcterms.source.isbn9781441970459
dcterms.source.placeHeidelberg
dcterms.source.chapter77
curtin.departmentDigital Ecosystems and Business Intelligence Institute (DEBII)
curtin.accessStatusFulltext not available


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