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ABSTRACT: Background
Chronic kidney disease (CKD) is characterized by progressive renal function loss, which may finally lead to end-stage renal disease (ESRD). The study is aimed at identifying crucial genes related to CKD progressive and constructing a disease prediction model to investigate risk factors.Methods
GSE97709 and GSE37171 datasets were downloaded from the GEO database including peripheral blood samples from subjects with CKD, ESRD, and healthy controls. Differential expressed genes (DEGs) were identified and functional enrichment analysis. Machine learning algorithm-based prediction model was constructed to identify crucial functional feature genes related to ESRD.Results
A total of 76 DEGs were screened from CDK vs. normal samples while 10,114 DEGs were identif
SUBMITTER: Xin G
PROVIDER: S-EPMC7676934 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature