227 related articles for article (PubMed ID: 30598639)
1. Analysis of dynamic molecular networks for pancreatic ductal adenocarcinoma progression.
Pan Z; Li L; Fang Q; Zhang Y; Hu X; Qian Y; Huang P
Cancer Cell Int; 2018; 18():214. PubMed ID: 30598639
[TBL] [Abstract][Full Text] [Related]
2. Identifying
Ding J; Liu Y; Lai Y
PeerJ; 2020; 8():e10419. PubMed ID: 33282565
[TBL] [Abstract][Full Text] [Related]
3. ITGA2, LAMB3, and LAMC2 may be the potential therapeutic targets in pancreatic ductal adenocarcinoma: an integrated bioinformatics analysis.
Islam S; Kitagawa T; Baron B; Abiko Y; Chiba I; Kuramitsu Y
Sci Rep; 2021 May; 11(1):10563. PubMed ID: 34007003
[TBL] [Abstract][Full Text] [Related]
4. Integrated transcriptome meta-analysis of pancreatic ductal adenocarcinoma and matched adjacent pancreatic tissues.
Atay S
PeerJ; 2020; 8():e10141. PubMed ID: 33194391
[TBL] [Abstract][Full Text] [Related]
5. Identification of potential target genes in pancreatic ductal adenocarcinoma by bioinformatics analysis.
Tang Y; Zhang Z; Tang Y; Chen X; Zhou J
Oncol Lett; 2018 Aug; 16(2):2453-2461. PubMed ID: 30013637
[TBL] [Abstract][Full Text] [Related]
6. Identification of hub genes and regulators associated with pancreatic ductal adenocarcinoma based on integrated gene expression profile analysis.
Shang M; Zhang L; Chen X; Zheng S
Discov Med; 2019 Sep; 28(153):159-172. PubMed ID: 31926587
[TBL] [Abstract][Full Text] [Related]
7. Analysis of molecular pathways in pancreatic ductal adenocarcinomas with a bioinformatics approach.
Wang Y; Li Y
Asian Pac J Cancer Prev; 2015; 16(6):2561-7. PubMed ID: 25824797
[TBL] [Abstract][Full Text] [Related]
8. Identification of differentially expressed genes in pancreatic ductal adenocarcinoma and normal pancreatic tissues based on microarray datasets.
Liu L; Wang S; Cen C; Peng S; Chen Y; Li X; Diao N; Li Q; Ma L; Han P
Mol Med Rep; 2019 Aug; 20(2):1901-1914. PubMed ID: 31257501
[TBL] [Abstract][Full Text] [Related]
9. Identification of hub genes and analysis of prognostic values in pancreatic ductal adenocarcinoma by integrated bioinformatics methods.
Lu Y; Li C; Chen H; Zhong W
Mol Biol Rep; 2018 Dec; 45(6):1799-1807. PubMed ID: 30173393
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Screening and validating the core biomarkers in patients with pancreatic ductal adenocarcinoma.
Li Y; Zhu YY; Dai GP; Wu DJ; Gao ZZ; Zhang L; Fan YH
Math Biosci Eng; 2019 Nov; 17(1):910-927. PubMed ID: 31731384
[TBL] [Abstract][Full Text] [Related]
12. Upregulation of ASPM, BUB1B and SPDL1 in tumor tissues predicts poor survival in patients with pancreatic ductal adenocarcinoma.
Tian X; Wang N
Oncol Lett; 2020 Apr; 19(4):3307-3315. PubMed ID: 32218868
[TBL] [Abstract][Full Text] [Related]
13. Four potential microRNAs affect the progression of pancreatic ductal adenocarcinoma by targeting MET via the PI3K/AKT signaling pathway.
Yao LC; Jiang XH; Yan SS; Wang W; Wu L; Zhai LL; Xiang F; Ji T; Ye L; Tang ZG
Oncol Lett; 2021 Apr; 21(4):326. PubMed ID: 33692858
[TBL] [Abstract][Full Text] [Related]
14. FN1, SPARC, and SERPINE1 are highly expressed and significantly related to a poor prognosis of gastric adenocarcinoma revealed by microarray and bioinformatics.
Li L; Zhu Z; Zhao Y; Zhang Q; Wu X; Miao B; Cao J; Fei S
Sci Rep; 2019 May; 9(1):7827. PubMed ID: 31127138
[TBL] [Abstract][Full Text] [Related]
15. Identification of potential hub genes associated with the pathogenesis and prognosis of pancreatic duct adenocarcinoma using bioinformatics meta-analysis of multi-platform datasets.
Ma Y; Pu Y; Peng L; Luo X; Xu J; Peng Y; Tang X
Oncol Lett; 2019 Dec; 18(6):6741-6751. PubMed ID: 31807183
[TBL] [Abstract][Full Text] [Related]
16. Comprehensive analysis of abnormal expression, prognostic value and oncogenic role of the hub gene FN1 in pancreatic ductal adenocarcinoma
Lei X; Chen G; Li J; Wen W; Gong J; Fu J
PeerJ; 2021; 9():e12141. PubMed ID: 34567847
[TBL] [Abstract][Full Text] [Related]
17. Identification of hub genes and potential molecular mechanisms in gastric cancer by integrated bioinformatics analysis.
Cao L; Chen Y; Zhang M; Xu DQ; Liu Y; Liu T; Liu SX; Wang P
PeerJ; 2018; 6():e5180. PubMed ID: 30002985
[TBL] [Abstract][Full Text] [Related]
18. Identification of key pathways and genes changes in pancreatic cancer cells (BXPC-3) after cross-talk with primary pancreatic stellate cells using bioinformatics analysis.
Tang D; Wu Q; Yuan Z; Xu J; Zhang H; Jin Z; Zhang Q; Xu M; Wang Z; Dai Z; Fang H; Li Z; Lin C; Shi C; Xu M; Sun X; Wang D
Neoplasma; 2019 Sep; 66(5):681-693. PubMed ID: 31169017
[TBL] [Abstract][Full Text] [Related]
19. Collagen family genes and related genes might be associated with prognosis of patients with gastric cancer: an integrated bioinformatics analysis and experimental validation.
Weng K; Huang Y; Deng H; Wang R; Luo S; Wu H; Chen J; Long M; Hao W
Transl Cancer Res; 2020 Oct; 9(10):6246-6262. PubMed ID: 35117235
[TBL] [Abstract][Full Text] [Related]
20. Identification of significant genes as prognostic markers and potential tumor suppressors in lung adenocarcinoma via bioinformatical analysis.
Lu M; Fan X; Liao W; Li Y; Ma L; Yuan M; Gu R; Wei Z; Wang C; Zhang H
BMC Cancer; 2021 May; 21(1):616. PubMed ID: 34039311
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]