These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

174 related articles for article (PubMed ID: 12762450)

  • 1. Selecting differentially expressed genes from microarray experiments.
    Pepe MS; Longton G; Anderson GL; Schummer M
    Biometrics; 2003 Mar; 59(1):133-42. PubMed ID: 12762450
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Arrow plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on sample subgroups.
    Silva-Fortes C; Amaral Turkman MA; Sousa L
    BMC Bioinformatics; 2012 Jun; 13():147. PubMed ID: 22734592
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Regularized binormal ROC method in disease classification using microarray data.
    Ma S; Song X; Huang J
    BMC Bioinformatics; 2006 May; 7():253. PubMed ID: 16684357
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Ranking analysis for identifying differentially expressed genes.
    Qi Y; Sun H; Sun Q; Pan L
    Genomics; 2011 May; 97(5):326-9. PubMed ID: 21402142
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A theoretical analysis of the selection of differentially expressed genes.
    Mukherjee S; Roberts SJ
    J Bioinform Comput Biol; 2005 Jun; 3(3):627-43. PubMed ID: 16108087
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Regularized gene selection in cancer microarray meta-analysis.
    Ma S; Huang J
    BMC Bioinformatics; 2009 Jan; 10():1. PubMed ID: 19118496
    [TBL] [Abstract][Full Text] [Related]  

  • 7. An integrated algorithm for gene selection and classification applied to microarray data of ovarian cancer.
    Lee ZJ
    Artif Intell Med; 2008 Jan; 42(1):81-93. PubMed ID: 18006289
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Identifying differentially expressed genes from microarray experiments via statistic synthesis.
    Yang YH; Xiao Y; Segal MR
    Bioinformatics; 2005 Apr; 21(7):1084-93. PubMed ID: 15513985
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Microarray data simulator for improved selection of differentially expressed genes.
    Singhal S; Kyvernitis CG; Johnson SW; Kaiser LR; Liebman MN; Albelda SM
    Cancer Biol Ther; 2003; 2(4):383-91. PubMed ID: 14508110
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Discovery of highly differentiative gene groups from microarray gene expression data using the gene club approach.
    Mao S; Dong G
    J Bioinform Comput Biol; 2005 Dec; 3(6):1263-80. PubMed ID: 16374906
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Nonparametric methods for identifying differentially expressed genes in microarray data.
    Troyanskaya OG; Garber ME; Brown PO; Botstein D; Altman RB
    Bioinformatics; 2002 Nov; 18(11):1454-61. PubMed ID: 12424116
    [TBL] [Abstract][Full Text] [Related]  

  • 12. MOST: detecting cancer differential gene expression.
    Lian H
    Biostatistics; 2008 Jul; 9(3):411-8. PubMed ID: 18048648
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments.
    Parodi S; Pistoia V; Muselli M
    BMC Bioinformatics; 2008 Oct; 9():410. PubMed ID: 18834513
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Sample size for detecting differentially expressed genes in microarray experiments.
    Wei C; Li J; Bumgarner RE
    BMC Genomics; 2004 Nov; 5():87. PubMed ID: 15533245
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A probabilistic approach for automated discovery of perturbed genes using expression data from microarray or RNA-Seq.
    Sundaramurthy G; Eghbalnia HR
    Comput Biol Med; 2015 Dec; 67():29-40. PubMed ID: 26492320
    [TBL] [Abstract][Full Text] [Related]  

  • 16. AUCTSP: an improved biomarker gene pair class predictor.
    Kagaris D; Khamesipour A; Yiannoutsos CT
    BMC Bioinformatics; 2018 Jun; 19(1):244. PubMed ID: 29940833
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Tumor classification ranking from microarray data.
    Hewett R; Kijsanayothin P
    BMC Genomics; 2008 Sep; 9 Suppl 2(Suppl 2):S21. PubMed ID: 18831787
    [TBL] [Abstract][Full Text] [Related]  

  • 18. An efficient semi-unsupervised gene selection method via spectral biclustering.
    Liu B; Wan C; Wang L
    IEEE Trans Nanobioscience; 2006 Jun; 5(2):110-4. PubMed ID: 16805107
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Leveraging two-way probe-level block design for identifying differential gene expression with high-density oligonucleotide arrays.
    Barrera L; Benner C; Tao YC; Winzeler E; Zhou Y
    BMC Bioinformatics; 2004 Apr; 5():42. PubMed ID: 15099405
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A nonparametric likelihood ratio test to identify differentially expressed genes from microarray data.
    Bokka S; Mathur SK
    Appl Bioinformatics; 2006; 5(4):267-76. PubMed ID: 17140273
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.