130 related articles for article (PubMed ID: 38013370)
21. 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]
22. Identification and validation of genes associated with copper death in oral squamous cell carcinoma based on machine learning and weighted gene co-expression network analysis.
Zhang M; Li Q; Zhang W; Yang Y; Gu J; Dong Q
J Stomatol Oral Maxillofac Surg; 2023 Dec; 124(6S):101561. PubMed ID: 37451513
[TBL] [Abstract][Full Text] [Related]
23. Screening of key genes in childhood asthma based on bioinformatics analysis.
Xia Y; Ling C; Zhan S
Transl Pediatr; 2023 May; 12(5):967-976. PubMed ID: 37305716
[TBL] [Abstract][Full Text] [Related]
24. Identification of potential biomarkers and immune-related pathways related to immune infiltration in patients with acute myocardial infarction.
Lin Z; Xu H; Chen Y; Zhang X; Yang J
Transpl Immunol; 2022 Oct; 74():101652. PubMed ID: 35764238
[TBL] [Abstract][Full Text] [Related]
25. Identification of immune-related genes in diagnosing retinopathy of prematurity with sepsis through bioinformatics analysis and machine learning.
Chen H; Chen E; Lu Y; Xu Y
Front Genet; 2023; 14():1264873. PubMed ID: 38028617
[No Abstract] [Full Text] [Related]
26. Exploration of biomarkers for systemic lupus erythematosus by machine-learning analysis.
Zhao X; Duan L; Cui D; Xie J
BMC Immunol; 2023 Nov; 24(1):44. PubMed ID: 37950194
[TBL] [Abstract][Full Text] [Related]
27. The shared biomarkers and pathways of systemic lupus erythematosus and metabolic syndrome analyzed by bioinformatics combining machine learning algorithm and single-cell sequencing analysis.
Wang Y; Huang Z; Xiao Y; Wan W; Yang X
Front Immunol; 2022; 13():1015882. PubMed ID: 36341378
[TBL] [Abstract][Full Text] [Related]
28. Identification of diagnostic markers for moyamoya disease by combining bulk RNA-sequencing analysis and machine learning.
Xu Y; Chen B; Guo Z; Chen C; Wang C; Zhou H; Zhang C; Feng Y
Sci Rep; 2024 Mar; 14(1):5931. PubMed ID: 38467737
[TBL] [Abstract][Full Text] [Related]
29. Immune-associated biomarkers identification for diagnosing carotid plaque progression with uremia through systematical bioinformatics and machine learning analysis.
Liu C; Tang L; Zhou Y; Tang X; Zhang G; Zhu Q; Zhou Y
Eur J Med Res; 2023 Feb; 28(1):92. PubMed ID: 36823662
[TBL] [Abstract][Full Text] [Related]
30. Identification of Immune-Associated Genes in Diagnosing Aortic Valve Calcification With Metabolic Syndrome by Integrated Bioinformatics Analysis and Machine Learning.
Zhou Y; Shi W; Zhao D; Xiao S; Wang K; Wang J
Front Immunol; 2022; 13():937886. PubMed ID: 35865542
[TBL] [Abstract][Full Text] [Related]
31. Identification of immune-related biomarkers in peripheral blood of schizophrenia using bioinformatic methods and machine learning algorithms.
Zhu X; Wang CL; Yu JF; Weng J; Han B; Liu Y; Tang X; Pan B
Front Cell Neurosci; 2023; 17():1256184. PubMed ID: 37841288
[TBL] [Abstract][Full Text] [Related]
32. Identification of cuproptosis-related asthma diagnostic genes by WGCNA analysis and machine learning.
Wang F; Su Q; Li C
J Asthma; 2023 Nov; 60(11):2052-2063. PubMed ID: 37289763
[TBL] [Abstract][Full Text] [Related]
33. Identification of SV2C and DENR as Key Biomarkers for Parkinson's Disease Based on Bioinformatics, Machine Learning, and Experimental Verification.
Wu J; Wu W; Jiang P; Xu Y; Yu M
J Mol Neurosci; 2024 Jan; 74(1):6. PubMed ID: 38189881
[TBL] [Abstract][Full Text] [Related]
34. Identification of diagnostic biomarkers in Alzheimer's disease by integrated bioinformatic analysis and machine learning strategies.
Jin B; Cheng X; Fei G; Sang S; Zhong C
Front Aging Neurosci; 2023; 15():1169620. PubMed ID: 37434738
[TBL] [Abstract][Full Text] [Related]
35. Screening of potential biomarkers in peripheral blood of patients with depression based on weighted gene co-expression network analysis and machine learning algorithms.
Wang Z; Meng Z; Chen C
Front Psychiatry; 2022; 13():1009911. PubMed ID: 36325528
[TBL] [Abstract][Full Text] [Related]
36. Identification of key modules and hub genes for eosinophilic asthma by weighted gene co-expression network analysis.
Li F; Li M; Hu L; Zhu W; Cheng D
J Asthma; 2023 May; 60(5):1038-1049. PubMed ID: 36165511
[TBL] [Abstract][Full Text] [Related]
37. Screening of novel biomarkers for breast cancer based on WGCNA and multiple machine learning algorithms.
Jin X; Huang Z; Guo P; Yuan R
Transl Cancer Res; 2023 Jun; 12(6):1466-1489. PubMed ID: 37434679
[TBL] [Abstract][Full Text] [Related]
38. 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]
39. Bioinformatic analysis and machine learning to identify the diagnostic biomarkers and immune infiltration in adenomyosis.
Liu D; Yin X; Guan X; Li K
Front Genet; 2022; 13():1082709. PubMed ID: 36685847
[No Abstract] [Full Text] [Related]
40. Identification of critical genes associated with the development of asthma by co-expression modules construction.
He LL; Xu F; Zhan XQ; Chen ZH; Shen HH
Mol Immunol; 2020 Jul; 123():18-25. PubMed ID: 32388106
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
