291 related articles for article (PubMed ID: 37779906)
1. Machine learning and bioinformatics analysis to identify autophagy-related biomarkers in peripheral blood for rheumatoid arthritis.
Dong G; Gao H; Chen Y; Yang H
Front Genet; 2023; 14():1238407. PubMed ID: 37779906
[No Abstract] [Full Text] [Related]
2. Identification of immune- and autophagy-related genes and effective diagnostic biomarkers in endometriosis: a bioinformatics analysis.
Ji X; Huang C; Mao H; Zhang Z; Zhang X; Yue B; Li X; Wu Q
Ann Transl Med; 2022 Dec; 10(24):1397. PubMed ID: 36660690
[TBL] [Abstract][Full Text] [Related]
3. Machine learning and weighted gene co-expression network analysis identify a three-gene signature to diagnose rheumatoid arthritis.
Wu YK; Liu CD; Liu C; Wu J; Xie ZG
Front Immunol; 2024; 15():1387311. PubMed ID: 38711508
[TBL] [Abstract][Full Text] [Related]
4. Identification and validation of metabolism-related genes signature and immune infiltration landscape of rheumatoid arthritis based on machine learning.
Guo Z; Ma Y; Wang Y; Xiang H; Cui H; Fan Z; Zhu Y; Xing D; Chen B; Tao H; Guo Z; Wu X
Aging (Albany NY); 2023 May; 15(9):3807-3825. PubMed ID: 37166429
[TBL] [Abstract][Full Text] [Related]
5. Identification of novel biomarkers and immune infiltration characteristics of ischemic stroke based on comprehensive bioinformatic analysis and machine learning.
Hu S; Cai J; Chen S; Wang Y; Ren L
Biochem Biophys Rep; 2024 Mar; 37():101595. PubMed ID: 38371524
[TBL] [Abstract][Full Text] [Related]
6. Identification of anoikis-related genes classification patterns and immune infiltration characterization in ischemic stroke based on machine learning.
Qin X; Yi S; Rong J; Lu H; Ji B; Zhang W; Ding R; Wu L; Chen Z
Front Aging Neurosci; 2023; 15():1142163. PubMed ID: 37032832
[TBL] [Abstract][Full Text] [Related]
7. Machine learning to identify immune-related biomarkers of rheumatoid arthritis based on WGCNA network.
Chen Y; Liao R; Yao Y; Wang Q; Fu L
Clin Rheumatol; 2022 Apr; 41(4):1057-1068. PubMed ID: 34767108
[TBL] [Abstract][Full Text] [Related]
8. Predicting diagnostic gene expression profiles associated with immune infiltration in patients with lupus nephritis.
Wang L; Yang Z; Yu H; Lin W; Wu R; Yang H; Yang K
Front Immunol; 2022; 13():839197. PubMed ID: 36532018
[TBL] [Abstract][Full Text] [Related]
9. Potential biomarkers and immune cell infiltration involved in aortic valve calcification identified through integrated bioinformatics analysis.
Lv X; Wang X; Liu J; Wang F; Sun M; Fan X; Ye Z; Liu P; Wen J
Front Physiol; 2022; 13():944551. PubMed ID: 36589450
[No Abstract] [Full Text] [Related]
10. Identification of TYR, TYRP1, DCT and LARP7 as related biomarkers and immune infiltration characteristics of vitiligo via comprehensive strategies.
Zhang J; Yu R; Guo X; Zou Y; Chen S; Zhou K; Chen Y; Li Y; Gao S; Wu Y
Bioengineered; 2021 Dec; 12(1):2214-2227. PubMed ID: 34107850
[TBL] [Abstract][Full Text] [Related]
11. Identifying potential biomarkers of idiopathic pulmonary fibrosis through machine learning analysis.
Wu Z; Chen H; Ke S; Mo L; Qiu M; Zhu G; Zhu W; Liu L
Sci Rep; 2023 Oct; 13(1):16559. PubMed ID: 37783761
[TBL] [Abstract][Full Text] [Related]
12. Bioinformatic analysis of related immune cell infiltration and key genes in the progression of osteonecrosis of the femoral head.
Duan X; Xing F; Zhang J; Li H; Chen Y; Lei Y; Zhao Y; Cao R; Guan H; Kong N; Li Y; Wu Z; Wang K; Tian R; Yang P
Front Immunol; 2023; 14():1340446. PubMed ID: 38283345
[TBL] [Abstract][Full Text] [Related]
13. Comprehensive molecular analyses of an autoimmune-related gene predictive model and immune infiltrations using machine learning methods in moyamoya disease.
Li S; Han Y; Zhang Q; Tang D; Li J; Weng L
Front Mol Biosci; 2022; 9():991425. PubMed ID: 36605987
[No Abstract] [Full Text] [Related]
14. Identification of immune-related genes in diagnosing atherosclerosis with rheumatoid arthritis through bioinformatics analysis and machine learning.
Liu F; Huang Y; Liu F; Wang H
Front Immunol; 2023; 14():1126647. PubMed ID: 36969166
[TBL] [Abstract][Full Text] [Related]
15. Identification and validation of novel biomarkers associated with immune infiltration for the diagnosis of osteosarcoma based on machine learning.
Ji Y; Lin Z; Li G; Tian X; Wu Y; Wan J; Liu T; Xu M
Front Genet; 2023; 14():1136783. PubMed ID: 37732314
[No Abstract] [Full Text] [Related]
16. Identification and Validation of the Diagnostic Characteristic Genes of Ovarian Cancer by Bioinformatics and Machine Learning.
Liu J; Liu L; Antwi PA; Luo Y; Liang F
Front Genet; 2022; 13():858466. PubMed ID: 35719392
[No Abstract] [Full Text] [Related]
17. Identifying Immune Cell Infiltration and Effective Diagnostic Biomarkers in Rheumatoid Arthritis by Bioinformatics Analysis.
Zhou S; Lu H; Xiong M
Front Immunol; 2021; 12():726747. PubMed ID: 34484236
[TBL] [Abstract][Full Text] [Related]
18. Construction and validation of a diagnostic model for rheumatoid arthritis based on mitochondrial autophagy-related genes.
In II; Deng W
Heliyon; 2024 Feb; 10(3):e24818. PubMed ID: 38327427
[TBL] [Abstract][Full Text] [Related]
19. Identification of diagnostic gene biomarkers and immune infiltration in patients with diabetic kidney disease using machine learning strategies and bioinformatic analysis.
Fu S; Cheng Y; Wang X; Huang J; Su S; Wu H; Yu J; Xu Z
Front Med (Lausanne); 2022; 9():918657. PubMed ID: 36250071
[TBL] [Abstract][Full Text] [Related]
20. The heat shock protein DNAJB2 as a novel biomarker for essential thrombocythemia diagnosis associated with immune infiltration.
Chen H; Lin C; Xue HM; Chen C; Yang M
Thromb Res; 2023 Mar; 223():131-138. PubMed ID: 36746103
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
