277 related articles for article (PubMed ID: 35739592)
1. ARG1 as a promising biomarker for sepsis diagnosis and prognosis: evidence from WGCNA and PPI network.
Zhang JX; Xu WH; Xing XH; Chen LL; Zhao QJ; Wang Y
Hereditas; 2022 Jun; 159(1):27. PubMed ID: 35739592
[TBL] [Abstract][Full Text] [Related]
2. Identification of key genes as potential diagnostic biomarkers in sepsis by bioinformatics analysis.
Lin G; Li N; Liu J; Sun J; Zhang H; Gui M; Zeng Y; Tang J
PeerJ; 2024; 12():e17542. PubMed ID: 38912048
[TBL] [Abstract][Full Text] [Related]
3. Identification of differentially expressed genes, transcription factors, microRNAs and pathways in neutrophils of sepsis patients through bioinformatics analysis.
Zheng Y; Peng L; He Z; Zou Z; Li F; Huang C; Li W
Cell Mol Biol (Noisy-le-grand); 2022 Feb; 67(5):405-420. PubMed ID: 35818227
[TBL] [Abstract][Full Text] [Related]
4. Identification of the Diagnostic Signature of Sepsis Based on Bioinformatic Analysis of Gene Expression and Machine Learning.
Zhao Q; Xu N; Guo H; Li J
Comb Chem High Throughput Screen; 2022; 25(1):21-28. PubMed ID: 33280594
[TBL] [Abstract][Full Text] [Related]
5. Screening of key genes related to the prognosis of mouse sepsis.
Chen M; Chen X; Hu Y; Cai X
Biosci Rep; 2020 Oct; 40(10):. PubMed ID: 33015708
[TBL] [Abstract][Full Text] [Related]
6. Identification of vital modules and genes associated with heart failure based on weighted gene coexpression network analysis.
Bian W; Wang Z; Li X; Jiang XX; Zhang H; Liu Z; Zhang DM
ESC Heart Fail; 2022 Apr; 9(2):1370-1379. PubMed ID: 35128826
[TBL] [Abstract][Full Text] [Related]
7.
Wang X; Wang LT; Yu B
Biomed Res Int; 2022; 2022():9463717. PubMed ID: 35445133
[TBL] [Abstract][Full Text] [Related]
8. miR‑148 family members are putative biomarkers for sepsis.
Dong L; Li H; Zhang S; Yang G
Mol Med Rep; 2019 Jun; 19(6):5133-5141. PubMed ID: 31059023
[TBL] [Abstract][Full Text] [Related]
9. Bioinformatics Analysis for Multiple Gene Expression Profiles in Sepsis.
Zhai J; Qi A; Zhang Y; Jiao L; Liu Y; Shou S
Med Sci Monit; 2020 Apr; 26():e920818. PubMed ID: 32280132
[TBL] [Abstract][Full Text] [Related]
10. Identification and Validation of a Dysregulated miRNA-Associated mRNA Network in Temporal Lobe Epilepsy.
Li X; Han Y; Li D; Yuan H; Huang S; Chen X; Qin Y
Biomed Res Int; 2021; 2021():4118216. PubMed ID: 34722763
[TBL] [Abstract][Full Text] [Related]
11. Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database.
Lu X; Xue L; Sun W; Ye J; Zhu Z; Mei H
Mol Med Rep; 2018 Feb; 17(2):3042-3054. PubMed ID: 29257295
[TBL] [Abstract][Full Text] [Related]
12. Network analysis of inflammatory responses to sepsis by neutrophils and peripheral blood mononuclear cells.
Godini R; Fallahi H; Ebrahimie E
PLoS One; 2018; 13(8):e0201674. PubMed ID: 30086151
[TBL] [Abstract][Full Text] [Related]
13. Evidence from Machine Learning, Diagnostic Hub Genes in Sepsis and Diagnostic Models based on Xgboost Models, Novel Molecular Models for the Diagnosis of Sepsis.
Yu Y; Li J; Li J; Zen X; Fu Q
Curr Med Chem; 2023 Oct; ():. PubMed ID: 37921181
[TBL] [Abstract][Full Text] [Related]
14. Bioinformatics Analysis of Gene Expression Profiles for Risk Prediction in Patients with Septic Shock.
Hu Y; Cheng L; Zhong W; Chen M; Zhang Q
Med Sci Monit; 2019 Dec; 25():9563-9571. PubMed ID: 31838482
[TBL] [Abstract][Full Text] [Related]
15. Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis.
Liang P; Wu Y; Qu S; Younis M; Wang W; Wu Z; Huang X
BMC Infect Dis; 2024 Jan; 24(1):32. PubMed ID: 38166628
[TBL] [Abstract][Full Text] [Related]
16. Identification of key genes and pathways in castrate-resistant prostate cancer by integrated bioinformatics analysis.
Wu YP; Ke ZB; Lin F; Wen YA; Chen S; Li XD; Chen SH; Sun XL; Huang JB; Zheng QS; Xue XY; Wei Y; Xu N
Pathol Res Pract; 2020 Oct; 216(10):153109. PubMed ID: 32853947
[TBL] [Abstract][Full Text] [Related]
17. Weighted Gene Co-Expression Network Analysis Identifies Hub Genes Associated with Occurrence and Prognosis of Oral Squamous Cell Carcinoma.
Ge Y; Li W; Ni Q; He Y; Chu J; Wei P
Med Sci Monit; 2019 Sep; 25():7272-7288. PubMed ID: 31562292
[TBL] [Abstract][Full Text] [Related]
18. Identification of genes related to consecutive trauma-induced sepsis via gene expression profiling analysis.
Dong L; Li H; Zhang S; Su L
Medicine (Baltimore); 2018 Apr; 97(15):e0362. PubMed ID: 29642183
[TBL] [Abstract][Full Text] [Related]
19. Identification of 40S ribosomal protein S8 as a novel biomarker for alcohol‑associated hepatocellular carcinoma using weighted gene co‑expression network analysis.
Bi N; Sun Y; Lei S; Zeng Z; Zhang Y; Sun C; Yu C
Oncol Rep; 2020 Aug; 44(2):611-627. PubMed ID: 32627011
[TBL] [Abstract][Full Text] [Related]
20. Bioinformatic analysis identifies potential biomarkers and therapeutic targets of septic-shock-associated acute kidney injury.
Tang Y; Yang X; Shu H; Yu Y; Pan S; Xu J; Shang Y
Hereditas; 2021 Apr; 158(1):13. PubMed ID: 33863396
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]