133 related articles for article (PubMed ID: 32441484)
1. Identification of the key genes associated with chemotherapy sensitivity in ovarian cancer patients.
Zheng H; Zhang M; Ma S; Yang W; Xie S; Wang Y; Liu Y; Kai J; Ma Q; Lu R; Guo L
Cancer Med; 2020 Jul; 9(14):5200-5209. PubMed ID: 32441484
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Prognostic values and prospective pathway signaling of MicroRNA-182 in ovarian cancer: a study based on gene expression omnibus (GEO) and bioinformatics analysis.
Li Y; Li L
J Ovarian Res; 2019 Nov; 12(1):106. PubMed ID: 31703725
[TBL] [Abstract][Full Text] [Related]
4. Identification of key biomarkers associated with development and prognosis in patients with ovarian carcinoma: evidence from bioinformatic analysis.
Shen J; Yu S; Sun X; Yin M; Fei J; Zhou J
J Ovarian Res; 2019 Nov; 12(1):110. PubMed ID: 31729978
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. Identification of significant genes with poor prognosis in ovarian cancer via bioinformatical analysis.
Feng H; Gu ZY; Li Q; Liu QH; Yang XY; Zhang JJ
J Ovarian Res; 2019 Apr; 12(1):35. PubMed ID: 31010415
[TBL] [Abstract][Full Text] [Related]
8. Construction of a novel prognostic-predicting model correlated to ovarian cancer.
Tang W; Li J; Chang X; Jia L; Tang Q; Wang Y; Zheng Y; Sun L; Feng Z
Biosci Rep; 2020 Aug; 40(8):. PubMed ID: 32716025
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. The identification of key biomarkers in patients with lung adenocarcinoma based on bioinformatics.
Ni KW; Sun GZ
Math Biosci Eng; 2019 Aug; 16(6):7671-7687. PubMed ID: 31698633
[TBL] [Abstract][Full Text] [Related]
11. Involvement of enhancer of zeste homolog 2 in cisplatin-resistance in ovarian cancer cells by interacting with several genes.
Wang H; Yu Y; Chen C; Wang Q; Huang T; Hong F; Zhu L
Mol Med Rep; 2015 Aug; 12(2):2503-10. PubMed ID: 25955318
[TBL] [Abstract][Full Text] [Related]
12. Profiling and bioinformatics analyses reveal differential circular RNA expression in ovarian cancer.
Wang J; Wu A; Yang B; Zhu X; Teng Y; Ai Z
Gene; 2020 Jan; 724():144150. PubMed ID: 31589961
[TBL] [Abstract][Full Text] [Related]
13. Gene expression profiling of epithelial ovarian cancer reveals key genes and pathways associated with chemotherapy resistance.
Zhang M; Luo SC
Genet Mol Res; 2016 Jan; 15(1):. PubMed ID: 26909918
[TBL] [Abstract][Full Text] [Related]
14. Investigation of hypoxia networks in ovarian cancer via bioinformatics analysis.
Zhang K; Kong X; Feng G; Xiang W; Chen L; Yang F; Cao C; Ding Y; Chen H; Chu M; Wang P; Zhang B
J Ovarian Res; 2018 Feb; 11(1):16. PubMed ID: 29482638
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Identification of Hub Genes in High-Grade Serous Ovarian Cancer Using Weighted Gene Co-Expression Network Analysis.
Wu M; Sun Y; Wu J; Liu G
Med Sci Monit; 2020 Mar; 26():e922107. PubMed ID: 32180586
[TBL] [Abstract][Full Text] [Related]
17. Identification of metastasis and prognosis-associated genes for serous ovarian cancer.
Yang Y; Qi S; Shi C; Han X; Yu J; Zhang L; Qin S; Gao Y
Biosci Rep; 2020 Jun; 40(6):. PubMed ID: 32510146
[TBL] [Abstract][Full Text] [Related]
18. Identification of Differentially Expressed Genes (DEGs) Relevant to Prognosis of Ovarian Cancer by Use of Integrated Bioinformatics Analysis and Validation by Immunohistochemistry Assay.
Zhang L; Sun L; Zhang B; Chen L
Med Sci Monit; 2019 Dec; 25():9902-9912. PubMed ID: 31871312
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. 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]
[Next] [New Search]