212 related articles for article (PubMed ID: 32443386)
21. Rhein suppresses esophageal cancer development by regulating cell cycle through DNMT3B gene.
Li C; Yu J; Feng Y; Sun X; Sun M; Ni W; Shao J; Wang B
Med Oncol; 2024 May; 41(6):153. PubMed ID: 38743323
[TBL] [Abstract][Full Text] [Related]
22. 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]
23. Identification of molecular marker associated with ovarian cancer prognosis using bioinformatics analysis and experiments.
Zheng MJ; Li X; Hu YX; Dong H; Gou R; Nie X; Liu Q; Ying-Ying H; Liu JJ; Lin B
J Cell Physiol; 2019 Jul; 234(7):11023-11036. PubMed ID: 30633343
[TBL] [Abstract][Full Text] [Related]
24. Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis.
Yu C; Chen F; Jiang J; Zhang H; Zhou M
Mol Med Rep; 2019 Aug; 20(2):1259-1269. PubMed ID: 31173250
[TBL] [Abstract][Full Text] [Related]
25. High expression of caspase-8 as a predictive factor of poor prognosis in patients with esophageal cancer.
Chai J; Lei Y; Xiang X; Ye J; Zhao H; Yi L
Cancer Med; 2023 Mar; 12(6):7651-7666. PubMed ID: 36533709
[TBL] [Abstract][Full Text] [Related]
26. Identification of differentially expressed genes between triple and non-triple-negative breast cancer using bioinformatics analysis.
Zhai Q; Li H; Sun L; Yuan Y; Wang X
Breast Cancer; 2019 Nov; 26(6):784-791. PubMed ID: 31197620
[TBL] [Abstract][Full Text] [Related]
27. Bioinformatics analysis of gene expression profiles of esophageal squamous cell carcinoma.
He Y; Liu J; Zhao Z; Zhao H
Dis Esophagus; 2017 May; 30(5):1-8. PubMed ID: 28375447
[TBL] [Abstract][Full Text] [Related]
28. Screening of potential key genes in esophageal cancer based on RBP and expression verification of HENMT1.
Reyimu A; Xing F; Zhou W; Zheng Y; Liu B; Dai J; Xing Y; Gao J
Medicine (Baltimore); 2023 Dec; 102(49):e36544. PubMed ID: 38065897
[TBL] [Abstract][Full Text] [Related]
29. Effects of EFNA1 on cell phenotype and prognosis of esophageal carcinoma.
Zhang Y; Zhang J; Pan G; Guan T; Zhang C; Hao A; Li Y; Ren H
World J Surg Oncol; 2021 Aug; 19(1):242. PubMed ID: 34399788
[TBL] [Abstract][Full Text] [Related]
30. Identification of Key Genes and Pathways in Cervical Cancer by Bioinformatics Analysis.
Wu X; Peng L; Zhang Y; Chen S; Lei Q; Li G; Zhang C
Int J Med Sci; 2019; 16(6):800-812. PubMed ID: 31337953
[TBL] [Abstract][Full Text] [Related]
31. Systematic investigation of the clinical significance and prognostic value of the CBXs in esophageal cancer.
Hou J; Yang Y; Gao H; Ouyang T; Liu Q; Ding R; Kan H
Medicine (Baltimore); 2022 Oct; 101(40):e30888. PubMed ID: 36221371
[TBL] [Abstract][Full Text] [Related]
32. The identification of a common different gene expression signature in patients with colorectal cancer.
Zhao ZW; Fan XX; Yang LL; Song JJ; Fang SJ; Tu JF; Chen MJ; Zheng LY; Wu FZ; Zhang DK; Ying XH; Ji JS
Math Biosci Eng; 2019 Apr; 16(4):2942-2958. PubMed ID: 31137244
[TBL] [Abstract][Full Text] [Related]
33. Identification of potential target genes and crucial pathways in small cell lung cancer based on bioinformatic strategy and human samples.
Chen X; Wang L; Su X; Luo SY; Tang X; Huang Y
PLoS One; 2020; 15(11):e0242194. PubMed ID: 33186389
[TBL] [Abstract][Full Text] [Related]
34. Screening and function analysis of hub genes and pathways in hepatocellular carcinoma via bioinformatics approaches.
Zhang L; Huang Y; Ling J; Zhuo W; Yu Z; Shao M; Luo Y; Zhu Y
Cancer Biomark; 2018; 22(3):511-521. PubMed ID: 29843214
[TBL] [Abstract][Full Text] [Related]
35. CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 May Be Potential Therapeutic Targets for Hepatocellular Carcinoma Using Integrated Bioinformatic Analysis.
Yang WX; Pan YY; You CG
Biomed Res Int; 2019; 2019():1245072. PubMed ID: 31737652
[TBL] [Abstract][Full Text] [Related]
36. Construction of an immune-related prognostic model and potential drugs screening for esophageal cancer based on bioinformatics analyses and network pharmacology.
Qi P; Qi B; Gu C; Huo S; Dang X; Liu Y; Zhao B
Immun Inflamm Dis; 2024 May; 12(5):e1266. PubMed ID: 38804848
[TBL] [Abstract][Full Text] [Related]
37. Weighted Gene Co-Expression Network Analysis Identifies Hub Genes Associated with Occurrence and Prognosis of Oral Squamous Cell Carcinoma.
Ge Y; Li W; Ni Q; He Y; Chu J; Wei P
Med Sci Monit; 2019 Sep; 25():7272-7288. PubMed ID: 31562292
[TBL] [Abstract][Full Text] [Related]
38. 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]
39. Metabolic subtypes and immune landscapes in esophageal squamous cell carcinoma: prognostic implications and potential for personalized therapies.
Yu XW; She PW; Chen FC; Chen YY; Zhou S; Wang XM; Lin XR; Liu QL; Huang ZJ; Qiu Y
BMC Cancer; 2024 Feb; 24(1):230. PubMed ID: 38373930
[TBL] [Abstract][Full Text] [Related]
40. Identification of Potential Biomarkers in Glioblastoma through Bioinformatic Analysis and Evaluating Their Prognostic Value.
Zhou Y; Yang L; Zhang X; Chen R; Chen X; Tang W; Zhang M
Biomed Res Int; 2019; 2019():6581576. PubMed ID: 31119182
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
