NDLI: Towards a methodology for Lipoprotein Ontology

Content Provider	IEEE Xplore Digital Library
Author	Meifania Chen Hadzic, M.
Copyright Year	2010
Description	Author affiliation: Research Lab for Digital Health Ecosystems, Curtin University of Technology, Perth, Australia (Meifania Chen; Hadzic, M.)
Abstract	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.
Starting Page	415
Ending Page	420
File Size	648016
Page Count	6
File Format	PDF
ISBN	9781424491674
ISSN	10637125
e-ISBN	9781424491681
DOI	10.1109/CBMS.2010.6042680
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-12
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ontologies Proteins Lipidomics Protein engineering Databases Semantics Vocabulary
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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