BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

266 related articles for article (PubMed ID: 15180936)

  • 1. A spline function approach for detecting differentially expressed genes in microarray data analysis.
    He W
    Bioinformatics; 2004 Nov; 20(17):2954-63. PubMed ID: 15180936
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Empirical Bayes screening of many p-values with applications to microarray studies.
    Datta S; Datta S
    Bioinformatics; 2005 May; 21(9):1987-94. PubMed ID: 15691856
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Classification of microarray data with factor mixture models.
    Martella F
    Bioinformatics; 2006 Jan; 22(2):202-8. PubMed ID: 16287938
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A new outlier removal approach for cDNA microarray normalization.
    Wu Y; Yan L; Liu H; Sun H; Xie H
    Biotechniques; 2009 Aug; 47(2):691-2, 694-700. PubMed ID: 19737130
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sample size for FDR-control in microarray data analysis.
    Jung SH
    Bioinformatics; 2005 Jul; 21(14):3097-104. PubMed ID: 15845654
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Modified nonparametric approaches to detecting differentially expressed genes in replicated microarray experiments.
    Zhao Y; Pan W
    Bioinformatics; 2003 Jun; 19(9):1046-54. PubMed ID: 12801864
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Detecting differentially expressed genes by relative entropy.
    Yan X; Deng M; Fung WK; Qian M
    J Theor Biol; 2005 Jun; 234(3):395-402. PubMed ID: 15784273
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Construction of null statistics in permutation-based multiple testing for multi-factorial microarray experiments.
    Gao X
    Bioinformatics; 2006 Jun; 22(12):1486-94. PubMed ID: 16574697
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A GMM-IG framework for selecting genes as expression panel biomarkers.
    Wang M; Chen JY
    Artif Intell Med; 2010; 48(2-3):75-82. PubMed ID: 20004087
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.
    Noma H; Matsui S
    Stat Med; 2013 May; 32(11):1904-16. PubMed ID: 23281021
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A non-transformation method for identifying differentially expressed genes from cDNA microarrays.
    Zhang JG; Yin ZJ; Zhang Q
    Yi Chuan Xue Bao; 2006 Jan; 33(1):80-8. PubMed ID: 16450591
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Estimating p-values in small microarray experiments.
    Yang H; Churchill G
    Bioinformatics; 2007 Jan; 23(1):38-43. PubMed ID: 17077100
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data.
    Shedden K; Chen W; Kuick R; Ghosh D; Macdonald J; Cho KR; Giordano TJ; Gruber SB; Fearon ER; Taylor JM; Hanash S
    BMC Bioinformatics; 2005 Feb; 6():26. PubMed ID: 15705192
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Ensemble dependence model for classification and prediction of cancer and normal gene expression data.
    Qiu P; Wang ZJ; Liu KJ
    Bioinformatics; 2005 Jul; 21(14):3114-21. PubMed ID: 15879455
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Practical FDR-based sample size calculations in microarray experiments.
    Hu J; Zou F; Wright FA
    Bioinformatics; 2005 Aug; 21(15):3264-72. PubMed ID: 15932903
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Non-linear tests for identifying differentially expressed genes or genetic networks.
    Xiong H
    Bioinformatics; 2006 Apr; 22(8):919-23. PubMed ID: 16473873
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Bias in the estimation of false discovery rate in microarray studies.
    Pawitan Y; Murthy KR; Michiels S; Ploner A
    Bioinformatics; 2005 Oct; 21(20):3865-72. PubMed ID: 16105901
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Identification of differentially expressed gene categories in microarray studies using nonparametric multivariate analysis.
    Nettleton D; Recknor J; Reecy JM
    Bioinformatics; 2008 Jan; 24(2):192-201. PubMed ID: 18042553
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.