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

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...

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Detalles Bibliográficos
Autores principales: Gao, Zhuo, S, Aishwarya, Li, Xiao-mei, Li, Xin-lun, Sui, Li-na
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Endocrinology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453249/
https://www.ncbi.nlm.nih.gov/pubmed/34557161
http://dx.doi.org/10.3389/fendo.2021.721202

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453249/
https://www.ncbi.nlm.nih.gov/pubmed/34557161
http://dx.doi.org/10.3389/fendo.2021.721202

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