Paper Infomation
Dynamic Network Biomarkers and Early Warning of Type 2 Diabetes
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Author: Hongling Liu, Yiping Lao, Wenqi Liu
Abstract: As a global chronic disease, type 2 diabetes has a serious impact on people's health. Its deterioration mechanism, critical early warning, early diagnosis and treatment strategies have been the focus of biomedical research. The emergence of this disease is usually due to an imbalance in the interaction network of biomolecules. Therefore, studying the dynamic changes of individual biomolecular networks is critical to revealing the pathogenesis of diabetes, in which the network differences of a single sample are particularly important, which helps to obtain early warning signals and key marker genes in the disease process. Based on high-dimensional omics data, using statistics, mathematics and computational biology knowledge, the early warning indicators and key biomarkers of type 2 diabetes were explored in depth. Through the combination of bulk 2 space and DNB algorithm, the identification process of critical points was optimized.
Keywords: Dynamic Network Biomarkers, Type 2 Diabetes, Critical State, Early Warning
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