BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

214 related articles for article (PubMed ID: 35272594)

  • 1. Identification and Verification of Potential Core Genes in Pediatric Septic Shock.
    Xu Z; Jiang M; Bai X; Ding L; Dong P; Jiang M
    Comb Chem High Throughput Screen; 2022; 25(13):2228-2239. PubMed ID: 35272594
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Six potential biomarkers in septic shock: a deep bioinformatics and prospective observational study.
    Kong C; Zhu Y; Xie X; Wu J; Qian M
    Front Immunol; 2023; 14():1184700. PubMed ID: 37359526
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. 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]  

  • 5. [Bioinformatics analysis and key gene verification of sepsis myocardial macrophage microarray data based on GEO database].
    Hu DX; Chen SS; Yu Y; Hu LL; Liu L; Yu LL
    Zhonghua Xin Xue Guan Bing Za Zhi; 2023 Jul; 51(7):759-768. PubMed ID: 37460430
    [No Abstract]   [Full Text] [Related]  

  • 6. Critical roles of S100A12, MMP9, and PRTN3 in sepsis diagnosis: Insights from multiple microarray data analyses.
    Zhang W
    Comput Biol Med; 2024 Mar; 171():108222. PubMed ID: 38447501
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Analysis of potential hub genes involved in the pathogenesis of Chinese type 1 diabetic patients.
    Yang S; Cao C; Xie Z; Zhou Z
    Ann Transl Med; 2020 Mar; 8(6):295. PubMed ID: 32355739
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Study on potential differentially expressed genes in stroke by bioinformatics analysis.
    Yang X; Wang P; Yan S; Wang G
    Neurol Sci; 2022 Feb; 43(2):1155-1166. PubMed ID: 34313877
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Identification of key genes and pathways using bioinformatics analysis in septic shock children.
    Yang J; Zhang S; Zhang J; Dong J; Wu J; Zhang L; Guo P; Tang S; Zhao Z; Wang H; Zhao Y; Zhang W; Wu F
    Infect Drug Resist; 2018; 11():1163-1174. PubMed ID: 30147344
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Analysis of signature genes and association with immune cells infiltration in pediatric septic shock.
    Fan J; Shi S; Qiu Y; Liu M; Shu Q
    Front Immunol; 2022; 13():1056750. PubMed ID: 36439140
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Renal tubular gen e biomarkers identification based on immune infiltrates in focal segmental glomerulosclerosis.
    Bai J; Pu X; Zhang Y; Dai E
    Ren Fail; 2022 Dec; 44(1):966-986. PubMed ID: 35713363
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Screening of potential biomarkers for distinguishing between latent and active tuberculosis in children using bioinformatics analysis.
    Shao M; Wu F; Zhang J; Dong J; Zhang H; Liu X; Liang S; Wu J; Zhang L; Zhang C; Zhang W
    Medicine (Baltimore); 2021 Feb; 100(5):e23207. PubMed ID: 33592820
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.
    Zhang C; Peng L; Zhang Y; Liu Z; Li W; Chen S; Li G
    Med Oncol; 2017 Jun; 34(6):101. PubMed ID: 28432618
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gastric cancer.
    Wu Q; Zhang B; Wang Z; Hu X; Sun Y; Xu R; Chen X; Wang Q; Ju F; Ren S; Zhang C; Qi F; Ma Q; Xue Q; Zhou YL
    Pathol Res Pract; 2019 May; 215(5):1038-1048. PubMed ID: 30975489
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Long Noncoding RNA THAP9-AS1 and TSPOAP1-AS1 Provide Potential Diagnostic Signatures for Pediatric Septic Shock.
    Wu Y; Yin Q; Zhang X; Zhu P; Luan H; Chen Y
    Biomed Res Int; 2020; 2020():7170464. PubMed ID: 33344646
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Bioinformatics analysis of differentially expressed genes involved in human developmental chondrogenesis.
    Zhou J; Li C; Yu A; Jie S; Du X; Liu T; Wang W; Luo Y
    Medicine (Baltimore); 2019 Jul; 98(27):e16240. PubMed ID: 31277141
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Crosstalk between septic shock and venous thromboembolism: a bioinformatics and immunoassay analysis.
    Li Z; Wang C; Zhang X; Xu X; Wang M; Dong L
    Front Cell Infect Microbiol; 2023; 13():1235269. PubMed ID: 38029239
    [TBL] [Abstract][Full Text] [Related]  

  • 19. [Bioinformatics analysis of ventilator-induced lung injury genome microarray based on gene expression omnibus database and key gene verification].
    Chen S; Zhang Y; Zhan Q
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2022 Jan; 34(1):41-47. PubMed ID: 35307059
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Identification of hub biomarkers and immune-related pathways participating in the progression of Kawasaki disease by integrated bioinformatics analysis.
    Gao Y; Tang X; Qian G; Huang H; Wang N; Wang Y; Zhuo W; Jiang J; Zheng Y; Li W; Liu Z; Li X; Xu L; Zhang J; Huang L; Liu Y; Lv H
    Immunobiology; 2023 Nov; 228(6):152750. PubMed ID: 37837870
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.