BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

205 related articles for article (PubMed ID: 37507655)

  • 1. Identification of crucial genes related to heart failure based on GEO database.
    Chen Y; Xue J; Yan X; Fang DG; Li F; Tian X; Yan P; Feng Z
    BMC Cardiovasc Disord; 2023 Jul; 23(1):376. PubMed ID: 37507655
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis.
    Kolur V; Vastrad B; Vastrad C; Kotturshetti S; Tengli A
    BMC Cardiovasc Disord; 2021 Jul; 21(1):329. PubMed ID: 34218797
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Identification of energy metabolism-related biomarkers for risk prediction of heart failure patients using random forest algorithm.
    Chen H; Jiang R; Huang W; Chen K; Zeng R; Wu H; Yang Q; Guo K; Li J; Wei R; Liao S; Tse HF; Sha W; Zhuo Z
    Front Cardiovasc Med; 2022; 9():993142. PubMed ID: 36304554
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Diagnosis and Prediction of Endometrial Carcinoma Using Machine Learning and Artificial Neural Networks Based on Public Databases.
    Zhao D; Zhang Z; Wang Z; Du Z; Wu M; Zhang T; Zhou J; Zhao W; Meng Y
    Genes (Basel); 2022 May; 13(6):. PubMed ID: 35741697
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Heart failure-related genes associated with oxidative stress and the immune landscape in lung cancer.
    Duan R; Ye K; Li Y; Sun Y; Zhu J; Ren J
    Front Immunol; 2023; 14():1167446. PubMed ID: 37275875
    [TBL] [Abstract][Full Text] [Related]  

  • 7. WGCNA combined with machine learning algorithms for analyzing key genes and immune cell infiltration in heart failure due to ischemic cardiomyopathy.
    Kong X; Sun H; Wei K; Meng L; Lv X; Liu C; Lin F; Gu X
    Front Cardiovasc Med; 2023; 10():1058834. PubMed ID: 37008314
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Integrated bioinformatics and machine learning algorithms reveal the critical cellular senescence-associated genes and immune infiltration in heart failure due to ischemic cardiomyopathy.
    Guo L; Xu CE
    Front Immunol; 2023; 14():1150304. PubMed ID: 37234159
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Identification of shared gene signatures and molecular mechanisms between chronic kidney disease and ulcerative colitis.
    Liang Z; Hu X; Lin R; Tang Z; Ye Z; Mao R; Chen W; Zhou Y
    Front Immunol; 2023; 14():1078310. PubMed ID: 36860851
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Integrative analyses of biomarkers and pathways for heart failure.
    Fan S; Hu Y
    BMC Med Genomics; 2022 Mar; 15(1):72. PubMed ID: 35346191
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Regulatory mechanism of fibrosis-related genes in patients with heart failure.
    Tao Y; Gao C; Qian D; Cao D; Han L; Yang L
    Front Genet; 2022; 13():1032572. PubMed ID: 36324504
    [No Abstract]   [Full Text] [Related]  

  • 12. Identification of 4 autophagy-related genes in heart failure by bioinformatics analysis and machine learning.
    Deng X; Yang Z; Li T; Wang Y; Yang Q; An R; Xu J
    Front Cardiovasc Med; 2024; 11():1247079. PubMed ID: 38347953
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Revealing immune infiltrate characteristics and potential immune-related genes in hepatic fibrosis: based on bioinformatics, transcriptomics and q-PCR experiments.
    Bai YM; Liang S; Zhou B
    Front Immunol; 2023; 14():1133543. PubMed ID: 37122694
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Integrating scRNA-seq to explore novel macrophage infiltration-associated biomarkers for diagnosis of heart failure.
    Li S; Ge T; Xu X; Xie L; Song S; Li R; Li H; Tong J
    BMC Cardiovasc Disord; 2023 Nov; 23(1):560. PubMed ID: 37974098
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis.
    Ganekal P; Vastrad B; Vastrad C; Kotrashetti S
    Ther Adv Cardiovasc Dis; 2023; 17():17539447231168471. PubMed ID: 37092838
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Identification of the potential biomarkers associated with circadian rhythms in heart failure.
    Sun Q; Zhao J; Liu L; Wang X; Gu X
    PeerJ; 2023; 11():e14734. PubMed ID: 36699999
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predicting potential biomarkers and immune infiltration characteristics in heart failure.
    Chen X; Zhang Q; Zhang Q
    Math Biosci Eng; 2022 Jun; 19(9):8671-8688. PubMed ID: 35942730
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Mining Potential Drug Targets and Constructing Diagnostic Models for Heart Failure Based on miRNA-mRNA Networks.
    Fang X; Song R; Wei J; Liao Q; Zeng Z
    Mediators Inflamm; 2022; 2022():9652169. PubMed ID: 36204659
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Establishment and Analysis of an Artificial Neural Network Model for Early Detection of Polycystic Ovary Syndrome Using Machine Learning Techniques.
    Wu Y; Xiao Q; Wang S; Xu H; Fang Y
    J Inflamm Res; 2023; 16():5667-5676. PubMed ID: 38050562
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Identification of common signature genes and pathways underlying the pathogenesis association between nonalcoholic fatty liver disease and atherosclerosis.
    Mo S; Wang Y; Yuan X; Wu W; Zhao H; Wei H; Qin H; Jiang H; Qin S
    Front Cardiovasc Med; 2023; 10():1142296. PubMed ID: 37063958
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.