Poster: Chronic disease prevention: A Translational Bioinformatics approach
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The socioeconomic transformations in the last decades and its consequent changes to societies lifestyle have increased the incidence of chronic diseases. Genomic medicine has suggested that the exposure to risk factors since conception may influence gene expression and consequently induce the development of chronic diseases in adulthood [?]. Scientific papers bringing up these discoveries indicate that epigenetics must be exploited in order to prevent diseases of high prevalence, such as cardiovascular diseases, diabetes and obesity. A large amount of scientific information burdens health care professionals interested in being updated, although, computational techniques might support management of large biomedical information repositories and discovery of knowledge. According to Butte [?], the effective transformation of results from biomedical research into knowledge that actually improves public health has been considered an important domain of informatics and has been called Translational Bioinformatics.
[1] Nikola K. Kasabov,et al. Ontology Based Personalized Modeling for Chronic Disease Risk Analysis: An Integrated Approach , 2008, Aust. J. Intell. Inf. Process. Syst..
[2] Atul J. Butte,et al. Viewpoint Paper: Translational Bioinformatics: Coming of Age , 2008, J. Am. Medical Informatics Assoc..