182 related articles for article (PubMed ID: 34908186)
1. Diabetic kidney disease-predisposing proinflammatory and profibrotic genes identified by weighted gene co-expression network analysis (WGCNA).
Chen J; Luo SF; Yuan X; Wang M; Yu HJ; Zhang Z; Yang YY
J Cell Biochem; 2022 Feb; 123(2):481-492. PubMed ID: 34908186
[TBL] [Abstract][Full Text] [Related]
2. Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network Analysis.
Wei R; Qiao J; Cui D; Pan Q; Guo L
Front Endocrinol (Lausanne); 2022; 13():883658. PubMed ID: 35721731
[TBL] [Abstract][Full Text] [Related]
3. Predicting diagnostic gene biomarkers in patients with diabetic kidney disease based on weighted gene co expression network analysis and machine learning algorithms.
Gao Q; Jin H; Xu W; Wang Y
Medicine (Baltimore); 2023 Oct; 102(43):e35618. PubMed ID: 37904449
[TBL] [Abstract][Full Text] [Related]
4. Identification of co-expressed central genes and transcription factors in acute myocardial infarction and diabetic nephropathy.
Li B; Zhao X; Xie W; Hong Z; Cao Y; Zhang Y; Ding Y
BMC Med Genomics; 2024 May; 17(1):134. PubMed ID: 38764052
[TBL] [Abstract][Full Text] [Related]
5. Apoptosis and NETotic cell death affect diabetic nephropathy independently: An study integrative study encompassing bioinformatics, machine learning, and experimental validation.
Cai H; Zeng Y; Luo D; Shao Y; Liu M; Wu J; Gao X; Zheng J; Zhou L; Liu F
Genomics; 2024 Jul; 116(4):110879. PubMed ID: 38851464
[TBL] [Abstract][Full Text] [Related]
6. Identification of potential key lipid metabolism-related genes involved in tubular injury in diabetic kidney disease by bioinformatics analysis.
Fan Y; He J; Shi L; Zhang M; Chen Y; Xu L; Han N; Jiang Y
Acta Diabetol; 2024 May; ():. PubMed ID: 38691241
[TBL] [Abstract][Full Text] [Related]
7. Identification and validation of immune and cuproptosis - related genes for diabetic nephropathy by WGCNA and machine learning.
Chen Y; Liao L; Wang B; Wu Z
Front Immunol; 2024; 15():1332279. PubMed ID: 38390317
[TBL] [Abstract][Full Text] [Related]
8. Identification of PDK4 as Hub Gene for Diabetic Nephropathy Using Co-Expression Network Analysis.
Han Y; Jin L; Wang L; Wei L; Tu C
Kidney Blood Press Res; 2023; 48(1):522-534. PubMed ID: 37385224
[TBL] [Abstract][Full Text] [Related]
9. Weighted gene co-expression network analysis of key targets and interventional mechanism of Milkvetch root in diabetic nephropathy.
Zeng SN; Li Y; Li YM; Wang SR
Eur Rev Med Pharmacol Sci; 2023 Oct; 27(20):9614-9627. PubMed ID: 37916327
[TBL] [Abstract][Full Text] [Related]
10. NET-Related Gene as Potential Diagnostic Biomarkers for Diabetic Tubulointerstitial Injury.
Liang Y; Lin J; Huang B; Weng M; Zhen T; Yang L; Chen Y; Li Q; Wan J
J Diabetes Res; 2024; 2024():4815488. PubMed ID: 38766319
[No Abstract] [Full Text] [Related]
11. FN1 and TGFBI are key biomarkers of macrophage immune injury in diabetic kidney disease.
Dou F; Liu Q; Lv S; Xu Q; Wang X; Liu S; Liu G
Medicine (Baltimore); 2023 Nov; 102(45):e35794. PubMed ID: 37960829
[TBL] [Abstract][Full Text] [Related]
12. Exploring the Immune Landscape of Cirrhosis through Weighted Gene Co-expression Network Analysis.
Zhuoma B; Yang C; Wang W; Ranhen Y
Cell Mol Biol (Noisy-le-grand); 2023 Jun; 69(6):168-174. PubMed ID: 37605574
[TBL] [Abstract][Full Text] [Related]
13. Integrated Analysis of Ferroptosis and Immunity-Related Genes Associated with Diabetic Kidney Disease.
Wang J; Wang L; Pang Z; Ge Q; Wu Y; Qi X
Diabetes Metab Syndr Obes; 2023; 16():3773-3793. PubMed ID: 38028994
[TBL] [Abstract][Full Text] [Related]
14. Identifying key genes for diabetic kidney disease by bioinformatics analysis.
Xu Y; Li L; Tang P; Zhang J; Zhong R; Luo J; Lin J; Zhang L
BMC Nephrol; 2023 Oct; 24(1):305. PubMed ID: 37853335
[TBL] [Abstract][Full Text] [Related]
15. Application of weighted gene co-expression network analysis to identify novel key genes in diabetic nephropathy.
Wang Z; Chen X; Li C; Tang W
J Diabetes Investig; 2022 Jan; 13(1):112-124. PubMed ID: 34245661
[TBL] [Abstract][Full Text] [Related]
16. Novel ferroptosis gene biomarkers and immune infiltration profiles in diabetic kidney disease via bioinformatics.
Huang Y; Yuan X
FASEB J; 2024 Jan; 38(2):e23421. PubMed ID: 38198194
[TBL] [Abstract][Full Text] [Related]
17. Mitochondrial-related hub genes in dermatomyositis: muscle and skin datasets-based identification and
Wang S; Tang Y; Chen X; Song S; Chen X; Zhou Q; Zeng L
Front Genet; 2024; 15():1325035. PubMed ID: 38389573
[No Abstract] [Full Text] [Related]
18. Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis.
Geng XD; Wang WW; Feng Z; Liu R; Cheng XL; Shen WJ; Dong ZY; Cai GY; Chen XM; Hong Q; Wu D
J Diabetes Investig; 2019 Jul; 10(4):972-984. PubMed ID: 30536626
[TBL] [Abstract][Full Text] [Related]
19. Single-Cell Sequencing Reveals the Expression of Immune-Related Genes in Macrophages of Diabetic Kidney Disease.
Shao X; Shi Y; Wang Y; Zhang L; Bai P; Wang J; Aniwan A; Lin Y; Zhou S; Yu P
Inflammation; 2024 Feb; 47(1):227-243. PubMed ID: 37777674
[TBL] [Abstract][Full Text] [Related]
20. Identification of key genes and biological regulatory mechanisms in diabetic nephropathy: Meta-analysis of gene expression datasets.
Hojjati F; Roointan A; Gholaminejad A; Eshraghi Y; Gheisari Y
Nefrologia (Engl Ed); 2023; 43(5):575-586. PubMed ID: 36681521
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
