A framework for lipoprotein ontology

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.