189 related articles for article (PubMed ID: 28407786)
1. Bioinformatics analysis to screen the key prognostic genes in ovarian cancer.
Li L; Cai S; Liu S; Feng H; Zhang J
J Ovarian Res; 2017 Apr; 10(1):27. PubMed ID: 28407786
[TBL] [Abstract][Full Text] [Related]
2. Identification of candidate biomarkers and analysis of prognostic values in ovarian cancer by integrated bioinformatics analysis.
Xu Z; Zhou Y; Cao Y; Dinh TL; Wan J; Zhao M
Med Oncol; 2016 Nov; 33(11):130. PubMed ID: 27757782
[TBL] [Abstract][Full Text] [Related]
3. A random forest classifier predicts recurrence risk in patients with ovarian cancer.
Cheng L; Li L; Wang L; Li X; Xing H; Zhou J
Mol Med Rep; 2018 Sep; 18(3):3289-3297. PubMed ID: 30066910
[TBL] [Abstract][Full Text] [Related]
4. Comprehensive bioinformatics analysis confirms RBMS3 as the central candidate biological target for ovarian cancer.
Wang M; Fu X; Wang W; Zhang Y; Jiang Z; Gu Y; Chu M; Shao Y; Li S
Med Eng Phys; 2022 Dec; 110():103883. PubMed ID: 36075788
[TBL] [Abstract][Full Text] [Related]
5. Establishment of a SVM classifier to predict recurrence of ovarian cancer.
Zhou J; Li L; Wang L; Li X; Xing H; Cheng L
Mol Med Rep; 2018 Oct; 18(4):3589-3598. PubMed ID: 30106117
[TBL] [Abstract][Full Text] [Related]
6. A network-pathway based module identification for predicting the prognosis of ovarian cancer patients.
Wang X; Wang SS; Zhou L; Yu L; Zhang LM
J Ovarian Res; 2016 Nov; 9(1):73. PubMed ID: 27806724
[TBL] [Abstract][Full Text] [Related]
7. A 19‑miRNA Support Vector Machine classifier and a 6‑miRNA risk score system designed for ovarian cancer patients.
Dong J; Xu M
Oncol Rep; 2019 Jun; 41(6):3233-3243. PubMed ID: 31002358
[TBL] [Abstract][Full Text] [Related]
8. Machine learning and bioinformatics models to identify gene expression patterns of ovarian cancer associated with disease progression and mortality.
Hossain MA; Saiful Islam SM; Quinn JMW; Huq F; Moni MA
J Biomed Inform; 2019 Dec; 100():103313. PubMed ID: 31655274
[TBL] [Abstract][Full Text] [Related]
9. Cross-validation of genes potentially associated with overall survival and drug resistance in ovarian cancer.
Gao Y; Liu X; Li T; Wei L; Yang A; Lu Y; Zhang J; Li L; Wang S; Yin F
Oncol Rep; 2017 May; 37(5):3084-3092. PubMed ID: 28350120
[TBL] [Abstract][Full Text] [Related]
10. Big data-based identification of methylated genes associated with drug resistance and prognosis in ovarian cancer.
Yan B; Xiong C; Huang F; Zhang M; Mo Y; Bai H
Medicine (Baltimore); 2020 Jul; 99(27):e20802. PubMed ID: 32629664
[TBL] [Abstract][Full Text] [Related]
11. The Value of the Stemness Index in Ovarian Cancer Prognosis.
Yuan H; Yu Q; Pang J; Chen Y; Sheng M; Tang W
Genes (Basel); 2022 May; 13(6):. PubMed ID: 35741755
[TBL] [Abstract][Full Text] [Related]
12. Upregulation of the long non-coding RNA SPRY4-IT1 indicates a poor prognosis and promotes tumorigenesis in ovarian cancer.
Li H; Liu C; Lu Z; Chen L; Wang J; Li Y; Ma H
Biomed Pharmacother; 2017 Apr; 88():529-534. PubMed ID: 28129625
[TBL] [Abstract][Full Text] [Related]
13. Implementing an online tool for genome-wide validation of survival-associated biomarkers in ovarian-cancer using microarray data from 1287 patients.
Gyorffy B; Lánczky A; Szállási Z
Endocr Relat Cancer; 2012 Apr; 19(2):197-208. PubMed ID: 22277193
[TBL] [Abstract][Full Text] [Related]
14. Increased expression of TET3 predicts unfavorable prognosis in patients with ovarian cancer-a bioinformatics integrative analysis.
Cao T; Pan W; Sun X; Shen H
J Ovarian Res; 2019 Oct; 12(1):101. PubMed ID: 31656201
[TBL] [Abstract][Full Text] [Related]
15. Adenylate kinase 7 is a prognostic indicator of overall survival in ovarian cancer.
Zhang XY; Zhou LL; Jiao Y; Li YQ; Guan YN; Zhao YC; Zheng LW
Medicine (Baltimore); 2021 Jan; 100(1):e24134. PubMed ID: 33429787
[TBL] [Abstract][Full Text] [Related]
16. Hsp90 is a potential risk factor for ovarian cancer prognosis: an evidence of a Chinese clinical center.
Duan C; Li K; Pan X; Wei Z; Xiao L
BMC Cancer; 2023 May; 23(1):489. PubMed ID: 37259027
[TBL] [Abstract][Full Text] [Related]
17. A thirteen‑gene set efficiently predicts the prognosis of glioblastoma.
Yang H; Jin L; Sun X
Mol Med Rep; 2019 Mar; 19(3):1613-1621. PubMed ID: 30628650
[TBL] [Abstract][Full Text] [Related]
18. Prognostic value of immune-related cells and genes in the tumor microenvironment of ovarian cancer, especially CST4.
Wang S; Wang C; Liu O; Hu Y; Li X; Lin B
Life Sci; 2021 Jul; 277():119461. PubMed ID: 33811900
[TBL] [Abstract][Full Text] [Related]
19. A prognostic 11 genes expression model for ovarian cancer.
Men CD; Liu QN; Ren Q
J Cell Biochem; 2018 Feb; 119(2):1971-1978. PubMed ID: 28817186
[TBL] [Abstract][Full Text] [Related]
20. Ovarian cancer classification and prognosis assessment model based on prognostic target genes in key microRNA-target gene networks.
Chen X; Li Y; He J
J Gene Med; 2024 Jan; 26(1):e3575. PubMed ID: 37548130
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
