205 related articles for article (PubMed ID: 32772911)
1. Screening of Hub Gene Targets for Lung Cancer via Microarray Data.
Su C; Liu WX; Wu LS; Dong TJ; Liu JF
Comb Chem High Throughput Screen; 2021; 24(2):269-285. PubMed ID: 32772911
[TBL] [Abstract][Full Text] [Related]
2. Integrated bioinformatics analysis of microarray data from the GEO database to identify the candidate genes linked to poor prognosis in lung adenocarcinoma.
Liu X; Li L; Xie X; Zhuang D; Hu C
Technol Health Care; 2023; 31(2):579-592. PubMed ID: 36336945
[TBL] [Abstract][Full Text] [Related]
3. Identification of six candidate genes for endometrial carcinoma by bioinformatics analysis.
Zhu Y; Shi L; Chen P; Zhang Y; Zhu T
World J Surg Oncol; 2020 Jul; 18(1):161. PubMed ID: 32641130
[TBL] [Abstract][Full Text] [Related]
4. Identification and validation of key genes associated with non-small-cell lung cancer.
Ma Q; Xu Y; Liao H; Cai Y; Xu L; Xiao D; Liu C; Pu W; Zhong X; Guo X
J Cell Physiol; 2019 Dec; 234(12):22742-22752. PubMed ID: 31127628
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Identification of Hub Genes and Pathways in Gastric Adenocarcinoma Based on Bioinformatics Analysis.
Qiu J; Sun M; Wang Y; Chen B
Med Sci Monit; 2020 Feb; 26():e920261. PubMed ID: 32058995
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. Identification of potential biomarkers of vascular calcification using bioinformatics analysis and validation
Chen C; Wu Y; Lu HL; Liu K; Qin X
PeerJ; 2022; 10():e13138. PubMed ID: 35313524
[TBL] [Abstract][Full Text] [Related]
10. Comprehensive Analysis of Candidate Diagnostic and Prognostic Biomarkers Associated with Lung Adenocarcinoma.
Li J; Liu X; Cui Z; Han G
Med Sci Monit; 2020 Jun; 26():e922070. PubMed ID: 32578582
[TBL] [Abstract][Full Text] [Related]
11. DNA methylation biomarkers for nasopharyngeal carcinoma.
Han B; Yang X; Zhang P; Zhang Y; Tu Y; He Z; Li Y; Yuan J; Dong Y; Hosseini DK; Zhou T; Sun H
PLoS One; 2020; 15(4):e0230524. PubMed ID: 32271791
[TBL] [Abstract][Full Text] [Related]
12. Identification of candidate biomarkers and pathways associated with SCLC by bioinformatics analysis.
Wen P; Chidanguro T; Shi Z; Gu H; Wang N; Wang T; Li Y; Gao J
Mol Med Rep; 2018 Aug; 18(2):1538-1550. PubMed ID: 29845250
[TBL] [Abstract][Full Text] [Related]
13. Estimation of Hub Genes and Infiltrating Immune Cells in Non-Smoking Females with Lung Adenocarcinoma by Integrated Bioinformatic Analysis.
Li J; Wang B; Li X; Zhu Y
Med Sci Monit; 2020 Jul; 26():e922680. PubMed ID: 32669531
[TBL] [Abstract][Full Text] [Related]
14. Weighted correlation network analysis identifies FN1, COL1A1 and SERPINE1 associated with the progression and prognosis of gastric cancer.
Zhao Q; Xie J; Xie J; Zhao R; Song C; Wang H; Rong J; Yan L; Song Y; Wang F; Xie Y
Cancer Biomark; 2021; 31(1):59-75. PubMed ID: 33780362
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. 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]
17. Identification of Hub Genes in Duchenne Muscular Dystrophy: Evidence from Bioinformatic Analysis.
Zhang R; Lv L; Ban W; Dang X; Zhang C
J Comput Biol; 2020 Jan; 27(1):1-8. PubMed ID: 31390219
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Exploration of estrogen receptor-associated hub genes and potential molecular mechanisms in non-smoking females with lung adenocarcinoma using integrated bioinformatics analysis.
Wang H; Zhang Z; Xu K; Wei S; Li L; Wang L
Oncol Lett; 2019 Nov; 18(5):4605-4612. PubMed ID: 31611968
[TBL] [Abstract][Full Text] [Related]
20. Integrated bioinformatics analysis reveals upregulated extracellular matrix hub genes in pancreatic cancer: Implications for diagnosis, prognosis, immune infiltration, and therapeutic strategies.
Mogal MR; Jame JA; Sohel M; Mozibullah M; Mahmod MR; Junayed A; Kar N; Arbia L; Al Mamun A; Sikder MA
Cancer Rep (Hoboken); 2024 Apr; 7(4):e2059. PubMed ID: 38639039
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]