Back to search

Article

Identifying Key Genes for Diabetic Kidney Disease by Bioinformatics Analysis

2023-03-23

Abstract excerpt

<h4>Background: </h4> There are no reliable molecular targets for early diagnosis and effective treatment in the clinical management of diabetic kidney disease (DKD). To identify novel gene factors underlying the progression of DKD. Methods The public transcriptomic datasets of the alloxan-induced DKD model and the streptozotocin-induced DKD model were retrieved to perform an integrative bioinformatic analysis of...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
afa60419-5ebd-566b-a11c-4f2c2d60eaca
DOI
10.21203/rs.3.rs-2560888/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Identifying Key Genes for Diabetic Kidney Disease by Bioinformatics AnalysisDOI 10.21203/rs.3.rs-2560888/v1
Bioinformatics prediction and experimental verification of key biomarkers for diabetic kidney disease based on transcriptome sequencing in miceSemantic proximity
Identification of Key Candidate Genes and Chemical Perturbagens in Diabetic Kidney Disease Using Integrated Bioinformatics AnalysisSemantic proximity
Single-cell RNA and transcriptome sequencing profiles identify immune-associated key genes in the development of diabetic kidney diseaseSemantic proximity
Identification of key genes for diabetic kidney disease using biological informatics methods.Semantic proximity
Screening and identification of key biomarkers in diabetic kidney disease and its complications: Evidence from bioinformatics and next generation sequencing data analysisSemantic proximity
Identification of basement membrane markers in diabetic kidney disease and immune infiltration by using bioinformatics analysis and experimental verificationSemantic proximity
The unique molecular mechanism of diabetic nephropathy: a bioinformatics analysis of over 250 microarray datasetsSemantic proximity
Identification and validation of immune-related biomarkers and potential regulators and therapeutic targets for diabetic kidney diseaseSemantic proximity
A comprehensive weighted gene co-expression network analysis uncovers potential targets in diabetic kidney diseaseSemantic proximity
Identification of key biomarkers in diabetic nephropathy via bioinformatic analysisSemantic proximity
Multiomics Analyses Identify AKR1A1 as a Biomarker for Diabetic Kidney DiseaseSemantic proximity
Identification of immune microenvironment and PANoptosis-related biomarkers in diabetic kidney disease: PSMB8 and PSMB9Semantic proximity
Select a neighboring publication to make it the new centre.