“Big Data” Approaches for Prevention of the Metabolic Syndrome - Jiang, Xinping; Yang, Zhang; Wang, Shuai; Deng, Shuanglin (Frontiers in Genetics, 2022)
Metabolic syndrome is characterized by the concurrence multiple metabolic disorders including abdominal obesity, elevated blood pressure, elevated blood glucose, high serum triglycerides, and low serum high-density lipoprotein (HDL). This condition affects roughly one third of American adults, significantly increasing the risk of cerebral-cardiovascular diseases, type- 2 diabetes and multiple cancers. Extensive data have been generated throughout the research targeted or related to the condition, hence a growing body of studies based on computational science have discovered new options in depicting clinically relevant patterns within its complexity from public health to molecular research. In this review we briefly summarize the recent advances in the study of pathogenesis and pathophysiology of metabolic syndrome, and methodology of computational research including the types of data source, data mining and analytic tools.