236 related articles for article (PubMed ID: 33708832)
1. Identification of novel prognostic genes of triple-negative breast cancer using meta-analysis and weighted gene co-expressed network analysis.
Cao W; Jiang Y; Ji X; Guan X; Lin Q; Ma L
Ann Transl Med; 2021 Feb; 9(3):205. PubMed ID: 33708832
[TBL] [Abstract][Full Text] [Related]
2. Identification of a five genes prognosis signature for triple-negative breast cancer using multi-omics methods and bioinformatics analysis.
Ma J; Chen C; Liu S; Ji J; Wu D; Huang P; Wei D; Fan Z; Ren L
Cancer Gene Ther; 2022 Nov; 29(11):1578-1589. PubMed ID: 35474355
[TBL] [Abstract][Full Text] [Related]
3. Novel biomarkers identified in triple-negative breast cancer through RNA-sequencing.
Chen YL; Wang K; Xie F; Zhuo ZL; Liu C; Yang Y; Wang S; Zhao XT
Clin Chim Acta; 2022 Jun; 531():302-308. PubMed ID: 35504321
[TBL] [Abstract][Full Text] [Related]
4. Identification of Key Prognostic Genes of Triple Negative Breast Cancer by LASSO-Based Machine Learning and Bioinformatics Analysis.
Chen DL; Cai JH; Wang CCN
Genes (Basel); 2022 May; 13(5):. PubMed ID: 35627287
[TBL] [Abstract][Full Text] [Related]
5. Identification of potential oncogenes in triple-negative breast cancer based on bioinformatics analyses.
Xiao X; Zhang Z; Luo R; Peng R; Sun Y; Wang J; Chen X
Oncol Lett; 2021 May; 21(5):363. PubMed ID: 33747220
[TBL] [Abstract][Full Text] [Related]
6. Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis.
Yuan Q; Zheng L; Liao Y; Wu G
World J Surg Oncol; 2021 Mar; 19(1):86. PubMed ID: 33757543
[TBL] [Abstract][Full Text] [Related]
7. Identification of Hub Genes and Pathways of Triple Negative Breast Cancer by Expression Profiles Analysis.
Li L; Huang H; Zhu M; Wu J
Cancer Manag Res; 2021; 13():2095-2104. PubMed ID: 33688252
[TBL] [Abstract][Full Text] [Related]
8. Identification of key genes as potential biomarkers for triple‑negative breast cancer using integrating genomics analysis.
Zhong G; Lou W; Shen Q; Yu K; Zheng Y
Mol Med Rep; 2020 Feb; 21(2):557-566. PubMed ID: 31974598
[TBL] [Abstract][Full Text] [Related]
9. Identification of five hub genes as monitoring biomarkers for breast cancer metastasis in silico.
Cai Y; Mei J; Xiao Z; Xu B; Jiang X; Zhang Y; Zhu Y
Hereditas; 2019; 156():20. PubMed ID: 31285741
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Hsa-mir-3163 and CCNB1 may be potential biomarkers and therapeutic targets for androgen receptor positive triple-negative breast cancer.
Qiu P; Guo Q; Yao Q; Chen J; Lin J
PLoS One; 2021; 16(11):e0254283. PubMed ID: 34797837
[TBL] [Abstract][Full Text] [Related]
12. Integrated network analysis and machine learning approach for the identification of key genes of triple-negative breast cancer.
Naorem LD; Muthaiyan M; Venkatesan A
J Cell Biochem; 2019 Apr; 120(4):6154-6167. PubMed ID: 30302816
[TBL] [Abstract][Full Text] [Related]
13. Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer.
Zhai X; Yang Z; Liu X; Dong Z; Zhou D
PeerJ; 2020; 8():e9975. PubMed ID: 33005492
[TBL] [Abstract][Full Text] [Related]
14. Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers.
Liu Y; Teng L; Fu S; Wang G; Li Z; Ding C; Wang H; Bi L
BMC Cancer; 2021 May; 21(1):644. PubMed ID: 34053447
[TBL] [Abstract][Full Text] [Related]
15. Identification of potential core genes in triple negative breast cancer using bioinformatics analysis.
Li MX; Jin LT; Wang TJ; Feng YJ; Pan CP; Zhao DM; Shao J
Onco Targets Ther; 2018; 11():4105-4112. PubMed ID: 30140156
[TBL] [Abstract][Full Text] [Related]
16. Molecular Features of Triple Negative Breast Cancer: Microarray Evidence and Further Integrated Analysis.
He J; Yang J; Chen W; Wu H; Yuan Z; Wang K; Li G; Sun J; Yu L
PLoS One; 2015; 10(6):e0129842. PubMed ID: 26103053
[TBL] [Abstract][Full Text] [Related]
17. Bioinformatics analysis of human kallikrein 5 (
Song Y; Bai G; Li X; Zhou L; Si Y; Liu X; Deng Y; Shi Y
Cancer Innov; 2023 Oct; 2(5):376-390. PubMed ID: 38090381
[TBL] [Abstract][Full Text] [Related]
18. Identification of Potential Key Genes Associated With the Pathogenesis, Metastasis, and Prognosis of Triple-Negative Breast Cancer on the Basis of Integrated Bioinformatics Analysis.
Zhao B; Xu Y; Zhao Y; Shen S; Sun Q
Front Oncol; 2020; 10():856. PubMed ID: 32596149
[No Abstract] [Full Text] [Related]
19. Investigation of Candidate Genes and Pathways in Basal/TNBC Patients by Integrated Analysis.
Liu Q; Song X; Liu Z; Yu Z
Technol Cancer Res Treat; 2021; 20():15330338211019506. PubMed ID: 34184566
[TBL] [Abstract][Full Text] [Related]
20. Prognostic genes of triple-negative breast cancer identified by weighted gene co-expression network analysis.
Bao L; Guo T; Wang J; Zhang K; Bao M
Oncol Lett; 2020 Jan; 19(1):127-138. PubMed ID: 31897123
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]