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Identification of Key Candidate Genes and Chemical Perturbagens in Diabetic Kidney Disease Using Integrated Bioinformatics Analysis

7 Sept 2021

Abstract excerpt

Globally, nearly 40 percent of all diabetic patients develop serious diabetic kidney disease (DKD). The identification of the potential early-stage biomarkers and elucidation of their underlying molecular mechanisms in DKD are required. In this study, we performed integrated bioinformatics analysis on the expression profiles GSE111154, GSE30528 and GSE30529 associated with early diabetic nephropathy (EDN),...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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PMID: 34557161
DOI: 10.3389/fendo.2021.721202

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