[HTML][HTML] Identification of hub genes in diabetic kidney disease via multiple-microarray analysis
Y Zhang, W Li, Y Zhou - Annals of Translational Medicine, 2020 - ncbi.nlm.nih.gov
Y Zhang, W Li, Y Zhou
Annals of Translational Medicine, 2020•ncbi.nlm.nih.govBackground Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease;
however, the underlying molecular mechanisms remain unclear. Recently, bioinformatics
analysis has provided a comprehensive insight toward the molecular mechanisms of DKD.
Here, we re-analyzed three mRNA microarray datasets including a single-cell RNA
sequencing (scRNA-seq) dataset, with the aim of identifying crucial genes correlated with
DKD and contribute to a better understanding of DKD pathogenesis. Methods
however, the underlying molecular mechanisms remain unclear. Recently, bioinformatics
analysis has provided a comprehensive insight toward the molecular mechanisms of DKD.
Here, we re-analyzed three mRNA microarray datasets including a single-cell RNA
sequencing (scRNA-seq) dataset, with the aim of identifying crucial genes correlated with
DKD and contribute to a better understanding of DKD pathogenesis. Methods
Abstract
Background
Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease; however, the underlying molecular mechanisms remain unclear. Recently, bioinformatics analysis has provided a comprehensive insight toward the molecular mechanisms of DKD. Here, we re-analyzed three mRNA microarray datasets including a single-cell RNA sequencing (scRNA-seq) dataset, with the aim of identifying crucial genes correlated with DKD and contribute to a better understanding of DKD pathogenesis.
Methods
ncbi.nlm.nih.gov