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    Results: 1 to 20 of 627

    1.

    A Population Proportion approach for ranking differentially expressed genes.

    Gadgil M.

    BMC Bioinformatics. 2008 Sep 18;9:380.PMID: 18801167 [PubMed - indexed for MEDLINE]Related articlesFree article

    2.

    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

    3.

    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

    4.

    Detecting differentially expressed genes by relative entropy.

    Yan X, Deng M, Fung WK, Qian M.

    J Theor Biol. 2005 Jun 7;234(3):395-402. Epub 2005 Jan 24.PMID: 15784273 [PubMed - indexed for MEDLINE]Related articles

    5.

    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.PMID: 12424116 [PubMed - indexed for MEDLINE]Related articlesFree article

    6.

    Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data.

    Jeffery IB, Higgins DG, Culhane AC.

    BMC Bioinformatics. 2006 Jul 26;7:359.PMID: 16872483 [PubMed - indexed for MEDLINE]Related articlesFree article

    7.

    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

    8.

    The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies.

    Shi L, Jones WD, Jensen RV, Harris SC, Perkins RG, Goodsaid FM, Guo L, Croner LJ, Boysen C, Fang H, Qian F, Amur S, Bao W, Barbacioru CC, Bertholet V, Cao XM, Chu TM, Collins PJ, Fan XH, Frueh FW, Fuscoe JC, Guo X, Han J, Herman D, Hong H, Kawasaki ES, Li QZ, Luo Y, Ma Y, Mei N, Peterson RL, Puri RK, Shippy R, Su Z, Sun YA, Sun H, Thorn B, Turpaz Y, Wang C, Wang SJ, Warrington JA, Willey JC, Wu J, Xie Q, Zhang L, Zhang L, Zhong S, Wolfinger RD, Tong W.

    BMC Bioinformatics. 2008 Aug 12;9 Suppl 9:S10.PMID: 18793455 [PubMed - indexed for MEDLINE]Related articlesFree article

    9.

    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

    10.

    Statistically consistent identification of differentially expressed genes in DNA chip data over the whole expression range: relative variance method.

    Stokić D, Wick N, Biely C, Gurnhofer E, Thurner S.

    Appl Bioinformatics. 2006;5(4):277-84.PMID: 17140274 [PubMed - indexed for MEDLINE]Related articles

    11.

    Empirical Bayes models for multiple probe type microarrays at the probe level.

    Astrand M, Mostad P, Rudemo M.

    BMC Bioinformatics. 2008 Mar 20;9:156.PMID: 18366694 [PubMed - indexed for MEDLINE]Related articlesFree article

    12.

    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

    13.

    Biological validation of differentially expressed genes in chronic lymphocytic leukemia identified by applying multiple statistical methods to oligonucleotide microarrays.

    Abruzzo LV, Wang J, Kapoor M, Medeiros LJ, Keating MJ, Edward Highsmith W, Barron LL, Cromwell CC, Coombes KR.

    J Mol Diagn. 2005 Aug;7(3):337-45.PMID: 16049305 [PubMed - indexed for MEDLINE]Related articlesFree article

    14.

    A two-sample Bayesian t-test for microarray data.

    Fox RJ, Dimmic MW.

    BMC Bioinformatics. 2006 Mar 10;7:126.PMID: 16529652 [PubMed - indexed for MEDLINE]Related articlesFree article

    15.

    Noise sampling method: an ANOVA approach allowing robust selection of differentially regulated genes measured by DNA microarrays.

    Draghici S, Kulaeva O, Hoff B, Petrov A, Shams S, Tainsky MA.

    Bioinformatics. 2003 Jul 22;19(11):1348-59.PMID: 12874046 [PubMed - indexed for MEDLINE]Related articlesFree article

    17.

    Modified nonparametric approaches to detecting differentially expressed genes in replicated microarray experiments.

    Zhao Y, Pan W.

    Bioinformatics. 2003 Jun 12;19(9):1046-54.PMID: 12801864 [PubMed - indexed for MEDLINE]Related articlesFree article

    18.

    The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data.

    Mansourian R, Mutch DM, Antille N, Aubert J, Fogel P, Le Goff JM, Moulin J, Petrov A, Rytz A, Voegel JJ, Roberts MA.

    Bioinformatics. 2004 Nov 1;20(16):2726-37. Epub 2004 May 14.PMID: 15145801 [PubMed - indexed for MEDLINE]Related articlesFree article

    19.

    Identifying differentially expressed genes in meta-analysis via Bayesian model-based clustering.

    Jung YY, Oh MS, Shin DW, Kang SH, Oh HS.

    Biom J. 2006 Jun;48(3):435-50.PMID: 16845907 [PubMed - indexed for MEDLINE]Related articles

    20.

    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

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