224 related articles for article (PubMed ID: 27911271)
1. Immunoglobulin superfamily genes are novel prognostic biomarkers for breast cancer.
Li Y; Guo M; Fu Z; Wang P; Zhang Y; Gao Y; Yue M; Ning S; Li D
Oncotarget; 2017 Jan; 8(2):2444-2456. PubMed ID: 27911271
[TBL] [Abstract][Full Text] [Related]
2. Integration of somatic mutation, expression and functional data reveals potential driver genes predictive of breast cancer survival.
Suo C; Hrydziuszko O; Lee D; Pramana S; Saputra D; Joshi H; Calza S; Pawitan Y
Bioinformatics; 2015 Aug; 31(16):2607-13. PubMed ID: 25810432
[TBL] [Abstract][Full Text] [Related]
3. Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).
Huan J; Wang L; Xing L; Qin X; Feng L; Pan X; Zhu L
Gene; 2014 Jan; 533(1):346-55. PubMed ID: 23978611
[TBL] [Abstract][Full Text] [Related]
4. Global Analysis of miRNA-mRNA Interaction Network in Breast Cancer with Brain Metastasis.
Li Z; Peng Z; Gu S; Zheng J; Feng D; Qin Q; He J
Anticancer Res; 2017 Aug; 37(8):4455-4468. PubMed ID: 28739740
[TBL] [Abstract][Full Text] [Related]
5. Genome-wide screen identifies a novel prognostic signature for breast cancer survival.
Mao XY; Lee MJ; Zhu J; Zhu C; Law SM; Snijders AM
Oncotarget; 2017 Feb; 8(8):14003-14016. PubMed ID: 28122328
[TBL] [Abstract][Full Text] [Related]
6. Screening of Prognostic Factors in Early-Onset Breast Cancer.
Yu Z; He Q; Xu G
Technol Cancer Res Treat; 2020; 19():1533033819893670. PubMed ID: 32028860
[TBL] [Abstract][Full Text] [Related]
7. Bioinformatics-Based Identification of Methylated-Differentially Expressed Genes and Related Pathways in Gastric Cancer.
Li H; Liu JW; Liu S; Yuan Y; Sun LP
Dig Dis Sci; 2017 Nov; 62(11):3029-3039. PubMed ID: 28914394
[TBL] [Abstract][Full Text] [Related]
8. An Integrative Approach for Identifying Network Biomarkers of Breast Cancer Subtypes Using Genomic, Interactomic, and Transcriptomic Data.
Firoozbakht F; Rezaeian I; D'agnillo M; Porter L; Rueda L; Ngom A
J Comput Biol; 2017 Aug; 24(8):756-766. PubMed ID: 28650678
[TBL] [Abstract][Full Text] [Related]
9. Identification of breast cancer candidate genes using gene co-expression and protein-protein interaction information.
Yue Z; Li HT; Yang Y; Hussain S; Zheng CH; Xia J; Chen Y
Oncotarget; 2016 Jun; 7(24):36092-36100. PubMed ID: 27150055
[TBL] [Abstract][Full Text] [Related]
10. Application of a co‑expression network for the analysis of aggressive and non‑aggressive breast cancer cell lines to predict the clinical outcome of patients.
Guo L; Zhang K; Bing Z
Mol Med Rep; 2017 Dec; 16(6):7967-7978. PubMed ID: 28944917
[TBL] [Abstract][Full Text] [Related]
11. The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes.
Lu X; Li X; Liu P; Qian X; Miao Q; Peng S
Molecules; 2018 Jan; 23(2):. PubMed ID: 29364829
[TBL] [Abstract][Full Text] [Related]
12. Identification of biomarkers associated with progression and prognosis in bladder cancer via co-expression analysis.
Shi S; Tian B
Cancer Biomark; 2019; 24(2):183-193. PubMed ID: 30689556
[TBL] [Abstract][Full Text] [Related]
13. Co-expression network analysis identified candidate biomarkers in association with progression and prognosis of breast cancer.
Zhou Q; Ren J; Hou J; Wang G; Ju L; Xiao Y; Gong Y
J Cancer Res Clin Oncol; 2019 Sep; 145(9):2383-2396. PubMed ID: 31280346
[TBL] [Abstract][Full Text] [Related]
14. Core module biomarker identification with network exploration for breast cancer metastasis.
Yang R; Daigle BJ; Petzold LR; Doyle FJ
BMC Bioinformatics; 2012 Jan; 13():12. PubMed ID: 22257533
[TBL] [Abstract][Full Text] [Related]
15. Systematic functional perturbations uncover a prognostic genetic network driving human breast cancer.
Gallenne T; Ross KN; Visser NL; Salony ; Desmet CJ; Wittner BS; Wessels LFA; Ramaswamy S; Peeper DS
Oncotarget; 2017 Mar; 8(13):20572-20587. PubMed ID: 28411283
[TBL] [Abstract][Full Text] [Related]
16. Weighted gene co-expression network analysis reveals key genes involved in pancreatic ductal adenocarcinoma development.
Giulietti M; Occhipinti G; Principato G; Piva F
Cell Oncol (Dordr); 2016 Aug; 39(4):379-88. PubMed ID: 27240826
[TBL] [Abstract][Full Text] [Related]
17. Analysis of the microarray gene expression for breast cancer progression after the application modified logistic regression.
Morais-Rodrigues F; Silv Erio-Machado R; Kato RB; Rodrigues DLN; Valdez-Baez J; Fonseca V; San EJ; Gomes LGR; Dos Santos RG; Vinicius Canário Viana M; da Cruz Ferraz Dutra J; Teixeira Dornelles Parise M; Parise D; Campos FF; de Souza SJ; Ortega JM; Barh D; Ghosh P; Azevedo VAC; Dos Santos MA
Gene; 2020 Feb; 726():144168. PubMed ID: 31759986
[TBL] [Abstract][Full Text] [Related]
18. Six novel immunoglobulin genes as biomarkers for better prognosis in triple-negative breast cancer by gene co-expression network analysis.
Hsu HM; Chu CM; Chang YJ; Yu JC; Chen CT; Jian CE; Lee CY; Chiang YT; Chang CW; Chang YT
Sci Rep; 2019 Mar; 9(1):4484. PubMed ID: 30872752
[TBL] [Abstract][Full Text] [Related]
19. Identifying cancer biomarkers by network-constrained support vector machines.
Chen L; Xuan J; Riggins RB; Clarke R; Wang Y
BMC Syst Biol; 2011 Oct; 5():161. PubMed ID: 21992556
[TBL] [Abstract][Full Text] [Related]
20. High-efficient Screening Method for Identification of Key Genes in Breast Cancer Through Microarray and Bioinformatics.
Liu Z; Liang G; Tan L; Su AN; Jiang W; Gong C
Anticancer Res; 2017 Aug; 37(8):4329-4335. PubMed ID: 28739725
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]