157 related articles for article (PubMed ID: 20487548)
1. Incorporating gene co-expression network in identification of cancer prognosis markers.
Ma S; Shi M; Li Y; Yi D; Shia BC
BMC Bioinformatics; 2010 May; 11():271. PubMed ID: 20487548
[TBL] [Abstract][Full Text] [Related]
2. Gene network-based cancer prognosis analysis with sparse boosting.
Ma S; Huang Y; Huang J; Fang K
Genet Res (Camb); 2012 Aug; 94(4):205-21. PubMed ID: 22950901
[TBL] [Abstract][Full Text] [Related]
3. Meta-analysis of Cancer Gene Profiling Data.
Roy J; Winter C; Schroeder M
Methods Mol Biol; 2016; 1381():211-22. PubMed ID: 26667463
[TBL] [Abstract][Full Text] [Related]
4. Incorporating prior biological knowledge for network-based differential gene expression analysis using differentially weighted graphical LASSO.
Zuo Y; Cui Y; Yu G; Li R; Ressom HW
BMC Bioinformatics; 2017 Feb; 18(1):99. PubMed ID: 28187708
[TBL] [Abstract][Full Text] [Related]
5. Differential Coexpression Network Analysis for Gene Expression Data.
Liu BH
Methods Mol Biol; 2018; 1754():155-165. PubMed ID: 29536442
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Functional genomics: improving cancer prognosis and drug development.
Mariani SM
MedGenMed; 2003 Mar; 5(1):18. PubMed ID: 12827079
[No Abstract] [Full Text] [Related]
8. Detection of gene pathways with predictive power for breast cancer prognosis.
Ma S; Kosorok MR
BMC Bioinformatics; 2010 Jan; 11():1. PubMed ID: 20043860
[TBL] [Abstract][Full Text] [Related]
9. Incorporating network structure in integrative analysis of cancer prognosis data.
Liu J; Huang J; Ma S
Genet Epidemiol; 2013 Feb; 37(2):173-83. PubMed ID: 23161517
[TBL] [Abstract][Full Text] [Related]
10. Incorporating higher-order representative features improves prediction in network-based cancer prognosis analysis.
Ma S; Kosorok MR; Huang J; Dai Y
BMC Med Genomics; 2011 Jan; 4():5. PubMed ID: 21226928
[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. 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]
13. Identification of Hub Genes Using Co-Expression Network Analysis in Breast Cancer as a Tool to Predict Different Stages.
Fu Y; Zhou QZ; Zhang XL; Wang ZZ; Wang P
Med Sci Monit; 2019 Nov; 25():8873-8890. PubMed ID: 31758680
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Whole genome profiling and other high throughput technologies in lymphoid neoplasms--current contributions and future hopes.
Campo E
Mod Pathol; 2013 Jan; 26 Suppl 1():S97-S110. PubMed ID: 23281439
[TBL] [Abstract][Full Text] [Related]
16. Drug Repositioning through Systematic Mining of Gene Coexpression Networks in Cancer.
Ivliev AE; 't Hoen PA; Borisevich D; Nikolsky Y; Sergeeva MG
PLoS One; 2016; 11(11):e0165059. PubMed ID: 27824868
[TBL] [Abstract][Full Text] [Related]
17. Prognosis related genes in HER2+ breast cancer based on weighted gene co-expression network analysis.
Weng Y; Jia R; Li Z; Liang W; Ji Y; Liang Y; Ning P
Chin Med J (Engl); 2023 May; 136(10):1258-1260. PubMed ID: 37104618
[No Abstract] [Full Text] [Related]
18. Improved cancer biomarkers identification using network-constrained infinite latent feature selection.
Cai L; Wu H; Zhou K
PLoS One; 2021; 16(2):e0246668. PubMed ID: 33571282
[TBL] [Abstract][Full Text] [Related]
19. Identification of breast cancer prognostic modules via differential module selection based on weighted gene Co-expression network analysis.
Guo L; Mao L; Lu W; Yang J
Biosystems; 2021 Jan; 199():104317. PubMed ID: 33279569
[TBL] [Abstract][Full Text] [Related]
20. An integrative approach to characterize disease-specific pathways and their coordination: a case study in cancer.
Xu M; Kao MC; Nunez-Iglesias J; Nevins JR; West M; Zhou XJ
BMC Genomics; 2008; 9 Suppl 1(Suppl 1):S12. PubMed ID: 18366601
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
