BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

218 related articles for article (PubMed ID: 31807166)

  • 21. Identification of candidate genes associated with the pathogenesis of small cell lung cancer via integrated bioinformatics analysis.
    Liao Y; Yin G; Wang X; Zhong P; Fan X; Huang C
    Oncol Lett; 2019 Oct; 18(4):3723-3733. PubMed ID: 31516585
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Bioinformatics analyses of significant genes, related pathways and candidate prognostic biomarkers in glioblastoma.
    Zhou L; Tang H; Wang F; Chen L; Ou S; Wu T; Xu J; Guo K
    Mol Med Rep; 2018 Nov; 18(5):4185-4196. PubMed ID: 30132538
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Bioinformatics analysis of gene expression profile data to screen key genes involved in intracranial aneurysms.
    Guo T; Hou D; Yu D
    Mol Med Rep; 2019 Nov; 20(5):4415-4424. PubMed ID: 31545495
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Screening Hub Genes as Prognostic Biomarkers of Hepatocellular Carcinoma by Bioinformatics Analysis.
    Zhou Z; Li Y; Hao H; Wang Y; Zhou Z; Wang Z; Chu X
    Cell Transplant; 2019 Dec; 28(1_suppl):76S-86S. PubMed ID: 31822116
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Identification of Key Biomarkers and Potential Molecular Mechanisms in Renal Cell Carcinoma by Bioinformatics Analysis.
    Li F; Guo P; Dong K; Guo P; Wang H; Lv X
    J Comput Biol; 2019 Nov; 26(11):1278-1295. PubMed ID: 31233342
    [No Abstract]   [Full Text] [Related]  

  • 26. Identifying hepatocellular carcinoma-related hub genes by bioinformatics analysis and CYP2C8 is a potential prognostic biomarker.
    Li C; Zhou D; Jiang X; Liu M; Tang H; Mei Z
    Gene; 2019 May; 698():9-18. PubMed ID: 30825595
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Identification of a three-gene-based prognostic model in multiple myeloma using bioinformatics analysis.
    Pan Y; Meng Y; Zhai Z; Xiong S
    PeerJ; 2021; 9():e11320. PubMed ID: 34249481
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Identification of CXCL13 as a potential biomarker in clear cell renal cell carcinoma via comprehensive bioinformatics analysis.
    Xu T; Ruan H; Song Z; Cao Q; Wang K; Bao L; Liu D; Tong J; Yang H; Chen K; Zhang X
    Biomed Pharmacother; 2019 Oct; 118():109264. PubMed ID: 31390578
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Identification of genes and pathways in esophageal adenocarcinoma using bioinformatics analysis.
    He F; Ai B; Tian L
    Biomed Rep; 2018 Oct; 9(4):305-312. PubMed ID: 30233782
    [TBL] [Abstract][Full Text] [Related]  

  • 30. 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]  

  • 31. Inactivation of ICAM1 inhibits metastasis and improves the prognosis of Ewing's sarcoma.
    Pan B; Bu X; Cao M; Zhang X; Huo T; Li Z; Gao X; Jing L; Luo X; Feng H; Yuan F; Guo K
    J Cancer Res Clin Oncol; 2021 Feb; 147(2):393-401. PubMed ID: 33104883
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Microarray gene expression profiling and bioinformatics analysis reveal key differentially expressed genes in clival and sacral chordoma cell lines.
    Li G; Cai L; Zhou L
    Neurol Res; 2019 Jun; 41(6):554-561. PubMed ID: 30821656
    [TBL] [Abstract][Full Text] [Related]  

  • 33. 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]  

  • 34. Glycolysis- and immune-related novel prognostic biomarkers of Ewing's sarcoma: glucuronic acid epimerase and triosephosphate isomerase 1.
    Jiang J; Zhan X; Xu G; Liang T; Yu C; Liao S; Chen L; Huang S; Sun X; Yi M; Zhang Z; Yao Y; Liu C
    Aging (Albany NY); 2021 Jul; 13(13):17516-17535. PubMed ID: 34233293
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Identification of biomarkers and mechanisms of diabetic cardiomyopathy using microarray data.
    Li H; Li X; Guo J; Wu G; Dong C; Pang Y; Gao S; Wang Y
    Cardiol J; 2020; 27(6):807-816. PubMed ID: 30246236
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Candidate genes and pathways associated with brain metastasis from lung cancer compared with lymph node metastasis.
    Zhao X; Wang N; Chidanguro T; Gu H; Li Y; Cao H; Wen P; Ren F
    Exp Ther Med; 2019 Aug; 18(2):1276-1284. PubMed ID: 31363372
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Identification of important invasion and proliferation related genes in adrenocortical carcinoma.
    Alshabi AM; Vastrad B; Shaikh IA; Vastrad C
    Med Oncol; 2019 Jul; 36(9):73. PubMed ID: 31321566
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Identifying the key genes and microRNAs in colorectal cancer liver metastasis by bioinformatics analysis and in vitro experiments.
    Zhang T; Guo J; Gu J; Wang Z; Wang G; Li H; Wang J
    Oncol Rep; 2019 Jan; 41(1):279-291. PubMed ID: 30542696
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Identification of biomarkers associated with diagnosis and prognosis of colorectal cancer patients based on integrated bioinformatics analysis.
    Chen L; Lu D; Sun K; Xu Y; Hu P; Li X; Xu F
    Gene; 2019 Apr; 692():119-125. PubMed ID: 30654001
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis.
    Zhou J; Hui X; Mao Y; Fan L
    Biosci Rep; 2019 Aug; 39(8):. PubMed ID: 31311829
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 11.