BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

101 related articles for article (PubMed ID: 21291417)

  • 1. A three component latent class model for robust semiparametric gene discovery.
    Alfo' M; Farcomeni A; Tardella L
    Stat Appl Genet Mol Biol; 2011; 10():Article 7. PubMed ID: 21291417
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Bayesian classification and non-Bayesian label estimation via EM algorithm to identify differentially expressed genes: a comparative study.
    Antunes M; Sousa L
    Biom J; 2008 Oct; 50(5):824-36. PubMed ID: 18932140
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A hierarchical semiparametric model for incorporating intergene information for analysis of genomic data.
    Qu L; Nettleton D; Dekkers JC
    Biometrics; 2012 Dec; 68(4):1168-77. PubMed ID: 22994883
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Robust semiparametric microarray normalization and significance analysis.
    Ma S; Kosorok MR; Huang J; Xie H; Manzella L; Soares MB
    Biometrics; 2006 Jun; 62(2):555-61. PubMed ID: 16918920
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Estimating the false discovery rate using nonparametric deconvolution.
    van de Wiel MA; Kim KI
    Biometrics; 2007 Sep; 63(3):806-15. PubMed ID: 17825012
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Shrinkage estimation of effect sizes as an alternative to hypothesis testing followed by estimation in high-dimensional biology: applications to differential gene expression.
    Montazeri Z; Yanofsky CM; Bickel DR
    Stat Appl Genet Mol Biol; 2010; 9():Article23. PubMed ID: 20597849
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Evaluation of a statistical equivalence test applied to microarray data.
    Qiu J; Cui X
    J Biopharm Stat; 2010 Mar; 20(2):240-66. PubMed ID: 20309757
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A mixture model with random-effects components for clustering correlated gene-expression profiles.
    Ng SK; McLachlan GJ; Wang K; Ben-Tovim Jones L; Ng SW
    Bioinformatics; 2006 Jul; 22(14):1745-52. PubMed ID: 16675467
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Sample size calculation through the incorporation of heteroscedasticity and dependence for a penalized t-statistic in microarray experiments.
    Hirakawa A; Hamada C; Yoshimura I
    J Biopharm Stat; 2012; 22(2):260-75. PubMed ID: 22251173
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Modeling microarray data using a threshold mixture model.
    Kauermann G; Eilers P
    Biometrics; 2004 Jun; 60(2):376-87. PubMed ID: 15180663
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A Laplace mixture model for identification of differential expression in microarray experiments.
    Bhowmick D; Davison AC; Goldstein DR; Ruffieux Y
    Biostatistics; 2006 Oct; 7(4):630-41. PubMed ID: 16565148
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.
    Ogunnaike BA; Gelmi CA; Edwards JS
    J Theor Biol; 2010 May; 264(2):211-22. PubMed ID: 20170665
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Detecting differential gene expression with a semiparametric hierarchical mixture method.
    Newton MA; Noueiry A; Sarkar D; Ahlquist P
    Biostatistics; 2004 Apr; 5(2):155-76. PubMed ID: 15054023
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Tail posterior probability for inference in pairwise and multiclass gene expression data.
    Bochkina N; Richardson S
    Biometrics; 2007 Dec; 63(4):1117-25. PubMed ID: 18078482
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Multivariate exploratory tools for microarray data analysis.
    Szabo A; Boucher K; Jones D; Tsodikov AD; Klebanov LB; Yakovlev AY
    Biostatistics; 2003 Oct; 4(4):555-67. PubMed ID: 14557111
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Identifying temporally differentially expressed genes through functional principal components analysis.
    Liu X; Yang MC
    Biostatistics; 2009 Oct; 10(4):667-79. PubMed ID: 19602570
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A two-step multiple comparison procedure for a large number of tests and multiple treatments.
    Jiang H; Doerge RW
    Stat Appl Genet Mol Biol; 2006; 5():Article28. PubMed ID: 17402912
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Autoregressive-model-based missing value estimation for DNA microarray time series data.
    Choong MK; Charbit M; Yan H
    IEEE Trans Inf Technol Biomed; 2009 Jan; 13(1):131-7. PubMed ID: 19129032
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.