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    Results: 1 to 20 of 2798

    1.

    MAID : an effect size based model for microarray data integration across laboratories and platforms.

    Borozan I, Chen L, Paeper B, Heathcote JE, Edwards AM, Katze M, Zhang Z, McGilvray ID.

    BMC Bioinformatics. 2008 Jul 10;9:305.PMID: 18616827 [PubMed - indexed for MEDLINE]Related articlesFree article

    2.

    Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models.

    Hu P, Greenwood CM, Beyene J.

    BMC Bioinformatics. 2005 May 27;6:128.PMID: 15921507 [PubMed - indexed for MEDLINE]Related articlesFree article

    3.

    Reproducibility of microarray data: a further analysis of microarray quality control (MAQC) data.

    Chen JJ, Hsueh HM, Delongchamp RR, Lin CJ, Tsai CA.

    BMC Bioinformatics. 2007 Oct 25;8:412.PMID: 17961233 [PubMed - indexed for MEDLINE]Related articlesFree article

    4.

    Novel and simple transformation algorithm for combining microarray data sets.

    Kim KY, Ki DH, Jeong HJ, Jeung HC, Chung HC, Rha SY.

    BMC Bioinformatics. 2007 Jun 25;8:218.PMID: 17588268 [PubMed - indexed for MEDLINE]Related articlesFree article

    5.

    Bayesian meta-analysis models for microarray data: a comparative study.

    Conlon EM, Song JJ, Liu A.

    BMC Bioinformatics. 2007 Mar 7;8:80.PMID: 17343745 [PubMed - indexed for MEDLINE]Related articlesFree article

    6.

    Microarray standard data set and figures of merit for comparing data processing methods and experiment designs.

    He YD, Dai H, Schadt EE, Cavet G, Edwards SW, Stepaniants SB, Duenwald S, Kleinhanz R, Jones AR, Shoemaker DD, Stoughton RB.

    Bioinformatics. 2003 May 22;19(8):956-65.PMID: 12761058 [PubMed - indexed for MEDLINE]Related articlesFree article

    7.

    Microarray data analysis: a practical approach for selecting differentially expressed genes.

    Mutch DM, Berger A, Mansourian R, Rytz A, Roberts MA.

    Genome Biol. 2001;2(12):PREPRINT0009. Epub 2001 Nov 16.PMID: 11790248 [PubMed - indexed for MEDLINE]Related articles

    8.

    Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package 'annotationTools'.

    Kuhn A, Luthi-Carter R, Delorenzi M.

    BMC Bioinformatics. 2008 Jan 17;9:26.PMID: 18201381 [PubMed - indexed for MEDLINE]Related articlesFree article

    9.

    Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes.

    Warnat P, Eils R, Brors B.

    BMC Bioinformatics. 2005 Nov 4;6:265.PMID: 16271137 [PubMed - indexed for MEDLINE]Related articlesFree article

    10.

    Sample size for detecting differentially expressed genes in microarray experiments.

    Wei C, Li J, Bumgarner RE.

    BMC Genomics. 2004 Nov 8;5(1):87.PMID: 15533245 [PubMed - indexed for MEDLINE]Related articlesFree article

    11.

    Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays.

    Wang Y, Barbacioru C, Hyland F, Xiao W, Hunkapiller KL, Blake J, Chan F, Gonzalez C, Zhang L, Samaha RR.

    BMC Genomics. 2006 Mar 21;7:59.PMID: 16551369 [PubMed - indexed for MEDLINE]Related articlesFree article

    12.

    Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data.

    Xu L, Tan AC, Naiman DQ, Geman D, Winslow RL.

    Bioinformatics. 2005 Oct 15;21(20):3905-11. Epub 2005 Aug 30.PMID: 16131522 [PubMed - indexed for MEDLINE]Related articlesFree article

    13.

    Combining multiple microarray studies and modeling interstudy variation.

    Choi JK, Yu U, Kim S, Yoo OJ.

    Bioinformatics. 2003;19 Suppl 1:i84-90.PMID: 12855442 [PubMed - indexed for MEDLINE]Related articlesFree article

    14.

    Reproducibility of differential gene detection across multiple microarray studies.

    Vo TM, Phan JH, Huynh KN, Wang MD.

    Conf Proc IEEE Eng Med Biol Soc. 2007;2007:4231-4.PMID: 18002936 [PubMed - indexed for MEDLINE]Related articles

    15.

    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

    16.

    Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration.

    Liang Y, Kelemen A.

    BMC Bioinformatics. 2008 Aug 28;9:354.PMID: 18755028 [PubMed - indexed for MEDLINE]Related articlesFree article

    17.

    Methods for evaluating gene expression from Affymetrix microarray datasets.

    Jiang N, Leach LJ, Hu X, Potokina E, Jia T, Druka A, Waugh R, Kearsey MJ, Luo ZW.

    BMC Bioinformatics. 2008 Jun 17;9:284.PMID: 18559105 [PubMed - indexed for MEDLINE]Related articlesFree article

    18.

    Statistical analysis of high-density oligonucleotide arrays: a multiplicative noise model.

    Sásik R, Calvo E, Corbeil J.

    Bioinformatics. 2002 Dec;18(12):1633-40.PMID: 12490448 [PubMed - indexed for MEDLINE]Related articlesFree article

    19.

    Cross-platform comparison and visualisation of gene expression data using co-inertia analysis.

    Culhane AC, Perrière G, Higgins DG.

    BMC Bioinformatics. 2003 Nov 21;4:59.PMID: 14633289 [PubMed - indexed for MEDLINE]Related articlesFree article

    20.

    Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets.

    Gormley M, Dampier W, Ertel A, Karacali B, Tozeren A.

    BMC Bioinformatics. 2007 Oct 26;8:415.PMID: 17963508 [PubMed - indexed for MEDLINE]Related articlesFree article

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