21^st Asia Pacific Diabetes Conference

Computational Approaches For Diabetes

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Diabetes is a common chronic disease that imposes considerable demands on the individual healthcare system. People with diabetes have a higher rate of cardiovascular disease than those without diabetes and are at increased risk for kidney failure, lower limb amputation and blindness. Obesity is a significant risk factor for diabetes and the prevalence of obesity in children and adults has dramatically increased in the past four decades. Diabetic dyslipidemia is one of the major risk factors for cardiovascular disease in diabetes mellitus. The characteristic features of diabetic dyslipidemia are a high plasma triglyceride concentration, low HDL cholesterol concentration and increased concentration of small dense LDL-cholesterol particles. In order to investigate the bioinformatics tools and methodologies used to in diabetes research, at first, this was difficult to do because it did not have a preconceived idea about how the research would be organized and how bioinformatics tools would be described or identified in the research. To get started, we ran several cursory searches using basic search terms such as bioinformatics and diabetes (research) through several databases to see what types of articles were returned.  Diabesity can be defined as a metabolic dysfunction that ranges from mild blood sugar imbalance to full-fledged type 2 diabetes.