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Journal Abstract Search

206 related items for PubMed ID: 39062507

  • 21. 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 04; 21(1):329. PubMed ID: 34218797
    [Abstract] [Full Text] [Related]

  • 22. Identification of 7 mitochondria-related genes as diagnostic biomarkers of MDD and their correlation with immune infiltration: New insights from bioinformatics analysis.
    Liu X, Wu Y, Li M.
    J Affect Disord; 2024 Mar 15; 349():86-100. PubMed ID: 38199392
    [Abstract] [Full Text] [Related]

  • 23. 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 Mar 15; 10():1058834. PubMed ID: 37008314
    [Abstract] [Full Text] [Related]

  • 24. Identification of novel biomarkers linking depressive disorder and Alzheimer's disease based on an integrative bioinformatics analysis.
    Song J, Ma Z, Zhang H, Liang T, Zhang J.
    BMC Genom Data; 2023 Apr 15; 24(1):22. PubMed ID: 37061663
    [Abstract] [Full Text] [Related]

  • 25. Screening for immune-related biomarkers associated with myasthenia gravis and dilated cardiomyopathy based on bioinformatics analysis and machine learning.
    Zhou G, Wang S, Lin L, Lu K, Lin Z, Zhang Z, Zhang Y, Cheng D, Szeto K, Peng R, Luo C.
    Heliyon; 2024 Apr 15; 10(7):e28446. PubMed ID: 38571624
    [Abstract] [Full Text] [Related]

  • 26. Bioinformatics and systems biology approach to identify the pathogenetic link of neurological pain and major depressive disorder.
    Hu J, Fu J, Cai Y, Chen S, Qu M, Zhang L, Fan W, Wang Z, Zeng Q, Zou J.
    Exp Biol Med (Maywood); 2024 Apr 15; 249():10129. PubMed ID: 38993198
    [Abstract] [Full Text] [Related]

  • 27. Identification of mitophagy-related biomarkers and immune infiltration in major depressive disorder.
    Zhang J, Xie S, Xiao R, Yang D, Zhan Z, Li Y.
    BMC Genomics; 2023 Apr 25; 24(1):216. PubMed ID: 37098514
    [Abstract] [Full Text] [Related]

  • 28. 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 Apr 25; 14():1264873. PubMed ID: 38028617
    [Abstract] [Full Text] [Related]

  • 29. Identification and validation of aging-related genes in heart failure based on multiple machine learning algorithms.
    Yu Y, Wang L, Hou W, Xue Y, Liu X, Li Y.
    Front Immunol; 2024 Apr 25; 15():1367235. PubMed ID: 38686376
    [Abstract] [Full Text] [Related]

  • 30. Investigating potential biomarkers of acute pancreatitis in patients with a BMI>30 using Mendelian randomization and transcriptomic analysis.
    Ji H, Tang Z, Jiang K, Lyu S, Zhao Y, Feng J, Dai R, Liang H.
    Lipids Health Dis; 2024 Apr 22; 23(1):119. PubMed ID: 38649912
    [Abstract] [Full Text] [Related]

  • 31. 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 22; 37():101595. PubMed ID: 38371524
    [Abstract] [Full Text] [Related]

  • 32. Immune-associated pivotal biomarkers identification and competing endogenous RNA network construction in post-operative atrial fibrillation by comprehensive bioinformatics and machine learning strategies.
    Zhou Y, Wu Q, Ni G, Hong Y, Xiao S, Liu C, Yu Z.
    Front Immunol; 2022 Mar 22; 13():974935. PubMed ID: 36341343
    [Abstract] [Full Text] [Related]

  • 33. Identifying potential biomarkers for non-obstructive azoospermia using WGCNA and machine learning algorithms.
    Tang Q, Su Q, Wei L, Wang K, Jiang T.
    Front Endocrinol (Lausanne); 2023 Mar 22; 14():1108616. PubMed ID: 37854191
    [Abstract] [Full Text] [Related]

  • 34. Screening COPD-Related Biomarkers and Traditional Chinese Medicine Prediction Based on Bioinformatics and Machine Learning.
    Cao Z, Zhao S, Hu S, Wu T, Sun F, Shi LI.
    Int J Chron Obstruct Pulmon Dis; 2024 Mar 22; 19():2073-2095. PubMed ID: 39346628
    [Abstract] [Full Text] [Related]

  • 35. A machine learning-based diagnostic model for myocardial infarction patients: Analysis of neutrophil extracellular traps-related genes and eQTL Mendelian randomization.
    Sheng M, Cui X.
    Medicine (Baltimore); 2024 Mar 22; 103(12):e37363. PubMed ID: 38518057
    [Abstract] [Full Text] [Related]

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  • 37. Integrated bioinformatics and machine learning strategies reveal PRDX6 as the key ferroptosis-associated molecular biosignature of heart failure.
    Jiang C, Jiang W.
    Gen Physiol Biophys; 2022 Sep 22; 41(5):365-380. PubMed ID: 36222336
    [Abstract] [Full Text] [Related]

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  • 39. A Positive Causal Effect of Shrimp Allergy on Major Depressive Disorder Mediated by Allergy- and Immune-Related Pathways in the East Asian Population.
    Rao S, Chen X, Ou OY, Chair SY, Chien WT, Liu G, Waye MMY.
    Nutrients; 2023 Dec 26; 16(1):. PubMed ID: 38201909
    [Abstract] [Full Text] [Related]

  • 40. Identification and validation of potential diagnostic signature and immune cell infiltration for HIRI based on cuproptosis-related genes through bioinformatics analysis and machine learning.
    Xiao F, Huang G, Yuan G, Li S, Wang Y, Tan Z, Liu Z, Tomlinson S, He S, Ouyang G, Zeng Y.
    Front Immunol; 2024 Dec 26; 15():1372441. PubMed ID: 38690269
    [Abstract] [Full Text] [Related]

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