BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

162 related articles for article (PubMed ID: 33761685)

  • 21. Identification of Key Biomarkers and Potential Molecular Mechanisms in Oral Squamous Cell Carcinoma by Bioinformatics Analysis.
    Yang B; Dong K; Guo P; Guo P; Jie G; Zhang G; Li T
    J Comput Biol; 2020 Jan; 27(1):40-54. PubMed ID: 31424263
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Identification of hub genes and construction of an mRNA-miRNA-lncRNA network of gastric carcinoma using integrated bioinformatics analysis.
    Wei G; Dong Y; He Z; Qiu H; Wu Y; Chen Y
    PLoS One; 2021; 16(12):e0261728. PubMed ID: 34968391
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Identification of key microRNAs and hub genes in non-small-cell lung cancer using integrative bioinformatics and functional analyses.
    Song F; Xuan Z; Yang X; Ye X; Pan Z; Fang Q
    J Cell Biochem; 2020 Mar; 121(3):2690-2703. PubMed ID: 31692035
    [TBL] [Abstract][Full Text] [Related]  

  • 24. The identification of key biomarkers in patients with lung adenocarcinoma based on bioinformatics.
    Ni KW; Sun GZ
    Math Biosci Eng; 2019 Aug; 16(6):7671-7687. PubMed ID: 31698633
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Identification of differential protein-coding gene expressions in early phase lung adenocarcinoma.
    Zhou LN; Li SC; Li XY; Ge H; Li HM
    Thorac Cancer; 2018 Feb; 9(2):234-240. PubMed ID: 29266838
    [TBL] [Abstract][Full Text] [Related]  

  • 26. TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer.
    Yang Q; Yu B; Sun J
    Biomed Res Int; 2020; 2020():4625123. PubMed ID: 33282948
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Identification of core genes and outcome in gastric cancer using bioinformatics analysis.
    Sun C; Yuan Q; Wu D; Meng X; Wang B
    Oncotarget; 2017 Sep; 8(41):70271-70280. PubMed ID: 29050278
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Identification of Potential Core Genes Associated With the Progression of Stomach Adenocarcinoma Using Bioinformatic Analysis.
    Yang B; Zhang M; Luo T
    Front Genet; 2020; 11():517362. PubMed ID: 33193601
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis.
    Dong S; Liang J; Zhai W; Yu Z
    Mol Genet Genomic Med; 2020 Mar; 8(3):e1126. PubMed ID: 31981472
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Identification of significant genes in non-small cell lung cancer by bioinformatics analyses.
    Ye X; Gao Q; Wu J; Zhou L; Tao M
    Transl Cancer Res; 2020 Jul; 9(7):4330-4340. PubMed ID: 35117799
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Identification of potential core genes in gastric cancer using bioinformatics analysis.
    Shao C; Wang R; Kong D; Gao Q; Xu C
    J Gastrointest Oncol; 2021 Oct; 12(5):2109-2122. PubMed ID: 34790378
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Analysis of genes associated with prognosis of lung adenocarcinoma based on GEO and TCGA databases.
    Yu Y; Tian X
    Medicine (Baltimore); 2020 May; 99(19):e20183. PubMed ID: 32384511
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Combined bioinformatics technology to explore pivot genes and related clinical prognosis in the development of gastric cancer.
    Xu J; Wang X; Ke Q; Liao K; Wan Y; Zhang K; Zhang G; Wang X
    Sci Rep; 2021 Jul; 11(1):15412. PubMed ID: 34326374
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Bioinformatics-Based Identification of Methylated-Differentially Expressed Genes and Related Pathways in Gastric Cancer.
    Li H; Liu JW; Liu S; Yuan Y; Sun LP
    Dig Dis Sci; 2017 Nov; 62(11):3029-3039. PubMed ID: 28914394
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Identification and Analysis of Key Genes Driving Gastric Cancer Through Bioinformatics.
    Liu Z; Liu S; Guo J; Sun L; Wang S; Wang Y; Qiu W; Lv J
    Genet Test Mol Biomarkers; 2021 Jan; 25(1):1-11. PubMed ID: 33470887
    [No Abstract]   [Full Text] [Related]  

  • 36. Common gene signatures and key pathways in hypopharyngeal and esophageal squamous cell carcinoma: Evidence from bioinformatic analysis.
    Zhou R; Liu D; Zhu J; Zhang T
    Medicine (Baltimore); 2020 Oct; 99(42):e22434. PubMed ID: 33080677
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Identification of significant genes with poor prognosis in ovarian cancer via bioinformatical analysis.
    Feng H; Gu ZY; Li Q; Liu QH; Yang XY; Zhang JJ
    J Ovarian Res; 2019 Apr; 12(1):35. PubMed ID: 31010415
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Identification of critical genes in gastric cancer to predict prognosis using bioinformatics analysis methods.
    Liu J; Ma L; Chen Z; Song Y; Gu T; Liu X; Zhao H; Yao N
    Ann Transl Med; 2020 Jul; 8(14):884. PubMed ID: 32793728
    [TBL] [Abstract][Full Text] [Related]  

  • 39. 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]  

  • 40. Genes That Predict Poor Prognosis in Breast Cancer via Bioinformatical Analysis.
    Zhou Q; Liu X; Lv M; Sun E; Lu X; Lu C
    Biomed Res Int; 2021; 2021():6649660. PubMed ID: 33959662
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.