941 related articles for article (PubMed ID: 34358255)
1. Screening and identification of key biomarkers of papillary renal cell carcinoma by bioinformatic analysis.
Xu Y; Kong D; Li Z; Qian L; Li J; Zou C
PLoS One; 2021; 16(8):e0254868. PubMed ID: 34358255
[TBL] [Abstract][Full Text] [Related]
2. Bioinformatics Study Identified EGF as a Crucial Gene in Papillary Renal Cell Cancer.
Qu G; Wang H; Tang C; Yang G; Xu Y
Dis Markers; 2022; 2022():4761803. PubMed ID: 35655917
[TBL] [Abstract][Full Text] [Related]
3. The underlying molecular mechanism and potential drugs for treatment in papillary renal cell carcinoma: A study based on TCGA and Cmap datasets.
Pang JS; Li ZK; Lin P; Wang XD; Chen G; Yan HB; Li SH
Oncol Rep; 2019 Apr; 41(4):2089-2102. PubMed ID: 30816528
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. Identification of EGFR as a Novel Key Gene in Clear Cell Renal Cell Carcinoma (ccRCC) through Bioinformatics Analysis and Meta-Analysis.
Wang S; Yu ZH; Chai KQ
Biomed Res Int; 2019; 2019():6480865. PubMed ID: 30895194
[TBL] [Abstract][Full Text] [Related]
7. Bioinformatics analysis and verification of gene targets for renal clear cell carcinoma.
Li F; Jin Y; Pei X; Guo P; Dong K; Wang H; Chen Y; Guo P; Meng LB; Wang Z
Comput Biol Chem; 2021 Jun; 92():107453. PubMed ID: 33636636
[TBL] [Abstract][Full Text] [Related]
8. Ceruloplasmin overexpression is associated with oncogenic pathways and poorer survival rates in clear-cell renal cell carcinoma.
Zhang Y; Chen Z; Chen JG; Chen XF; Gu DH; Liu ZM; Gao YD; Zheng B
FEBS Open Bio; 2021 Nov; 11(11):2988-3004. PubMed ID: 34449964
[TBL] [Abstract][Full Text] [Related]
9. Identification of 4-genes model in papillary renal cell tumor microenvironment based on comprehensive analysis.
Luo L; Zhou H; Su H
BMC Cancer; 2021 May; 21(1):553. PubMed ID: 33993869
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Integrated bioinformatics analysis for the screening of hub genes and therapeutic drugs in ovarian cancer.
Yang D; He Y; Wu B; Deng Y; Wang N; Li M; Liu Y
J Ovarian Res; 2020 Jan; 13(1):10. PubMed ID: 31987036
[TBL] [Abstract][Full Text] [Related]
12. Bioinformatics Analysis of Candidate Genes and Pathways Related to Hepatocellular Carcinoma in China: A Study Based on Public Databases.
Zhang P; Feng J; Wu X; Chu W; Zhang Y; Li P
Pathol Oncol Res; 2021; 27():588532. PubMed ID: 34257537
[No Abstract] [Full Text] [Related]
13. Integrated Analysis of Hub Genes and Pathways In Esophageal Carcinoma Based on NCBI's Gene Expression Omnibus (GEO) Database: A Bioinformatics Analysis.
Yu-Jing T; Wen-Jing T; Biao T
Med Sci Monit; 2020 Aug; 26():e923934. PubMed ID: 32756534
[TBL] [Abstract][Full Text] [Related]
14. Identification of key genes and signalling pathways in clear cell renal cell carcinoma: An integrated bioinformatics approach.
S V; Balasubramanian S; Perumal E; Santhakumar K
Cancer Biomark; 2024; 40(1):111-123. PubMed ID: 38427469
[TBL] [Abstract][Full Text] [Related]
15. Bioinformatics analysis of C3 and CXCR4 demonstrates their potential as prognostic biomarkers in clear cell renal cell carcinoma (ccRCC).
Quan J; Bai Y; Yang Y; Han EL; Bai H; Zhang Q; Zhang D
BMC Cancer; 2021 Jul; 21(1):814. PubMed ID: 34266404
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Identification of hub genes and pathways in adrenocortical carcinoma by integrated bioinformatic analysis.
Guo J; Gu Y; Ma X; Zhang L; Li H; Yan Z; Han Y; Xie L; Guo X
J Cell Mol Med; 2020 Apr; 24(8):4428-4438. PubMed ID: 32147961
[TBL] [Abstract][Full Text] [Related]
18. Screening, identification and validation of CCND1 and PECAM1/CD31 for predicting prognosis in renal cell carcinoma patients.
Yang JF; Shi SN; Xu WH; Qiu YH; Zheng JZ; Yu K; Song XY; Li F; Wang Y; Wang R; Qu YY; Zhang HL; Zhou XQ
Aging (Albany NY); 2019 Dec; 11(24):12057-12079. PubMed ID: 31850854
[TBL] [Abstract][Full Text] [Related]
19. Correlating Transcriptional Networks to Papillary Renal Cell Carcinoma Survival: A Large-Scale Coexpression Analysis and Clinical Validation.
Feng X; Zhang M; Meng J; Wang Y; Liu Y; Liang C; Fan S
Oncol Res; 2020 May; 28(3):285-297. PubMed ID: 31948514
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
