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    Results: 1 to 20 of 806

    1.

    Ranking analysis of F-statistics for microarray data.

    Tan YD, Fornage M, Xu H.

    BMC Bioinformatics. 2008 Mar 6;9:142.PMID: 18325100 [PubMed - indexed for MEDLINE]Related articlesFree article

    2.

    Construction of null statistics in permutation-based multiple testing for multi-factorial microarray experiments.

    Gao X.

    Bioinformatics. 2006 Jun 15;22(12):1486-94. Epub 2006 Mar 30.PMID: 16574697 [PubMed - indexed for MEDLINE]Related articlesFree article

    3.

    Ranking analysis of microarray data: a powerful method for identifying differentially expressed genes.

    Tan YD, Fornage M, Fu YX.

    Genomics. 2006 Dec;88(6):846-54. Epub 2006 Sep 18.PMID: 16979869 [PubMed - indexed for MEDLINE]Related articlesFree article

    4.

    A unified framework for finding differentially expressed genes from microarray experiments.

    Shaik JS, Yeasin M.

    BMC Bioinformatics. 2007 Sep 18;8:347.PMID: 17877806 [PubMed - indexed for MEDLINE]Related articlesFree article

    5.

    A generalized likelihood ratio test to identify differentially expressed genes from microarray data.

    Wang S, Ethier S.

    Bioinformatics. 2004 Jan 1;20(1):100-4.PMID: 14693815 [PubMed - indexed for MEDLINE]Related articlesFree article

    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 10;6:26.PMID: 15705192 [PubMed - indexed for MEDLINE]Related articlesFree article

    7.

    A mixture model approach to sample size estimation in two-sample comparative microarray experiments.

    Jørstad TS, Midelfart H, Bones AM.

    BMC Bioinformatics. 2008 Feb 25;9:117.PMID: 18298817 [PubMed - indexed for MEDLINE]Related articlesFree article

    8.

    Using weighted permutation scores to detect differential gene expression with microarray data.

    Guo X, Pan W.

    J Bioinform Comput Biol. 2005 Aug;3(4):989-1006.PMID: 16078371 [PubMed - indexed for MEDLINE]Related articles

    9.

    Tail posterior probability for inference in pairwise and multiclass gene expression data.

    Bochkina N, Richardson S.

    Biometrics. 2007 Dec;63(4):1117-25.PMID: 18078482 [PubMed - indexed for MEDLINE]Related articles

    10.

    Multidimensional local false discovery rate for microarray studies.

    Ploner A, Calza S, Gusnanto A, Pawitan Y.

    Bioinformatics. 2006 Mar 1;22(5):556-65. Epub 2005 Dec 20.PMID: 16368770 [PubMed - indexed for MEDLINE]Related articlesFree article

    11.

    Practical FDR-based sample size calculations in microarray experiments.

    Hu J, Zou F, Wright FA.

    Bioinformatics. 2005 Aug 1;21(15):3264-72. Epub 2005 Jun 2.PMID: 15932903 [PubMed - indexed for MEDLINE]Related articlesFree article

    12.

    Sample size for FDR-control in microarray data analysis.

    Jung SH.

    Bioinformatics. 2005 Jul 15;21(14):3097-104. Epub 2005 Apr 21.PMID: 15845654 [PubMed - indexed for MEDLINE]Related articlesFree article

    13.

    Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments.

    Zhao H, Chan KL, Cheng LM, Yan H.

    BMC Bioinformatics. 2008;9 Suppl 1:S9.PMID: 18315862 [PubMed - indexed for MEDLINE]Related articlesFree article

    14.

    The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison.

    Sioson AA, Mane SP, Li P, Sha W, Heath LS, Bohnert HJ, Grene R.

    BMC Bioinformatics. 2006 Apr 20;7:215.PMID: 16626497 [PubMed - indexed for MEDLINE]Related articlesFree article

    15.

    Identifying differentially expressed genes from microarray experiments via statistic synthesis.

    Yang YH, Xiao Y, Segal MR.

    Bioinformatics. 2005 Apr 1;21(7):1084-93. Epub 2004 Oct 28.PMID: 15513985 [PubMed - indexed for MEDLINE]Related articlesFree article

    16.

    A note on using permutation-based false discovery rate estimates to compare different analysis methods for microarray data.

    Xie Y, Pan W, Khodursky AB.

    Bioinformatics. 2005 Dec 1;21(23):4280-8. Epub 2005 Sep 27.PMID: 16188930 [PubMed - indexed for MEDLINE]Related articlesFree article

    17.

    Re-sampling strategy to improve the estimation of number of null hypotheses in FDR control under strong correlation structures.

    Lu X, Perkins DL.

    BMC Bioinformatics. 2007 May 18;8:157.PMID: 17509157 [PubMed - indexed for MEDLINE]Related articlesFree article

    18.

    Bayesian models for pooling microarray studies with multiple sources of replications.

    Conlon EM, Song JJ, Liu JS.

    BMC Bioinformatics. 2006 May 5;7:247.PMID: 16677390 [PubMed - indexed for MEDLINE]Related articlesFree article

    19.

    On the identification of differentially expressed genes: improving the generalized F-statistics for Affymetrix microarray gene expression data.

    Lai Y.

    Comput Biol Chem. 2006 Oct;30(5):321-6. Epub 2006 Sep 18.PMID: 16979381 [PubMed - indexed for MEDLINE]Related articles

    20.

    Estimating the false discovery rate using nonparametric deconvolution.

    van de Wiel MA, Kim KI.

    Biometrics. 2007 Sep;63(3):806-15.PMID: 17825012 [PubMed - indexed for MEDLINE]Related articles

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