Abstract-The advances of high throughput research in the biomedical domain have resulted in an onslaught of data being generated at an exponential rate. As a result, researchers face challenges in navigating through overwhelming amounts of information in order to derive relevant scientific insights. Ontologies address these issues by providing explicit description of biomedical entities and a platform for the integration of data, thereby enabling a more efficient retrieval of information. There have been major efforts in the development of biomedical ontologies in the recent years; however no such ontology exists for lipoproteins, which play a crucial role in various biological and cellular functions. Dysregulation in lipoprotein metabolism is significantly associated with an increased risk to cardiovascular disease, the leading cause of mortality in the world today. The aim of this paper is to propose a preliminary framework for Lipoprotein Ontology, with particular focus on the etiology and treatment of lipoprotein dysregulation. This may provide a novel and effective strategy for managing at risk individuals.

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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.