Abstract
Hypertrophic cardiomyopathy (HCM) is a complex genetic disease characterized by a variable clinical presentation and onset, as well as a high number of associated mutations.
Therefore, this disease is a good candidate for a translational medicine approach to assist in its prognosis. For this purpose, we propose a framework containing two components: one for data integration, and another for data analysis based on clinical-genetic associations obtained with data mining techniques.
In this article we present the implementation of the first component. At its basis is a semantic data model developed in OWL representing the clinical and genetic data necessary for the characterization of HCM patients. This model follows a modular approach and includes mappings to controlled vocabularies such as the NCI Thesaurus and SNOMED-Clinical Terms.
The development of the model has been done in collaboration with biomedical experts, who are also the providers of the data to populate it.
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Machado, C.M., Couto, F.M., Fernandes, A.R., Santos, S., Freitas, A.T. (2012). Toward a Translational Medicine Approach for Hypertrophic Cardiomyopathy. In: Böhm, C., Khuri, S., Lhotská, L., Renda, M.E. (eds) Information Technology in Bio- and Medical Informatics. ITBAM 2012. Lecture Notes in Computer Science, vol 7451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32395-9_12
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DOI: https://doi.org/10.1007/978-3-642-32395-9_12
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