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Items: 1 to 20 of 146

1.

Probe-level measurement error improves accuracy in detecting differential gene expression.

Liu X, Milo M, Lawrence ND, Rattray M.

Bioinformatics. 2006 Sep 1;22(17):2107-13. Epub 2006 Jul 4.

PMID:
16820429
2.

A tractable probabilistic model for Affymetrix probe-level analysis across multiple chips.

Liu X, Milo M, Lawrence ND, Rattray M.

Bioinformatics. 2005 Sep 15;21(18):3637-44. Epub 2005 Jul 14.

PMID:
16020470
3.

Including probe-level uncertainty in model-based gene expression clustering.

Liu X, Lin KK, Andersen B, Rattray M.

BMC Bioinformatics. 2007 Mar 21;8:98.

4.

Including probe-level measurement error in robust mixture clustering of replicated microarray gene expression.

Liu X, Rattray M.

Stat Appl Genet Mol Biol. 2010;9:Article42. doi: 10.2202/1544-6115.1600. Epub 2010 Dec 9.

PMID:
21194414
5.

Interactively optimizing signal-to-noise ratios in expression profiling: project-specific algorithm selection and detection p-value weighting in Affymetrix microarrays.

Seo J, Bakay M, Chen YW, Hilmer S, Shneiderman B, Hoffman EP.

Bioinformatics. 2004 Nov 1;20(16):2534-44. Epub 2004 Apr 29.

PMID:
15117752
6.

puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.

Liu X, Gao Z, Zhang L, Rattray M.

BMC Bioinformatics. 2013 Feb 5;14:39. doi: 10.1186/1471-2105-14-39.

7.

Gene selection for oligonucleotide array: an approach using PM probe level data.

Chen DT, Lin SH, Soong SJ.

Bioinformatics. 2004 Apr 12;20(6):854-62. Epub 2004 Jan 29.

PMID:
14752002
8.

A new summarization method for Affymetrix probe level data.

Hochreiter S, Clevert DA, Obermayer K.

Bioinformatics. 2006 Apr 15;22(8):943-9. Epub 2006 Feb 10.

PMID:
16473874
9.

BGX: a Bioconductor package for the Bayesian integrated analysis of Affymetrix GeneChips.

Turro E, Bochkina N, Hein AM, Richardson S.

BMC Bioinformatics. 2007 Nov 12;8:439.

10.

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. doi: 10.1186/1471-2105-9-284.

11.

CrossChip: a system supporting comparative analysis of different generations of Affymetrix arrays.

Kong SW, Hwang KB, Kim RD, Zhang BT, Greenberg SA, Kohane IS, Park PJ.

Bioinformatics. 2005 May 1;21(9):2116-7. Epub 2005 Jan 31.

13.

SScore: an R package for detecting differential gene expression without gene expression summaries.

Kennedy RE, Kerns RT, Kong X, Archer KJ, Miles MF.

Bioinformatics. 2006 May 15;22(10):1272-4. Epub 2006 Mar 30.

PMID:
16574698
14.

Bayesian hierarchical error model for analysis of gene expression data.

Cho H, Lee JK.

Bioinformatics. 2004 Sep 1;20(13):2016-25. Epub 2004 Mar 25.

PMID:
15044230
15.

affy--analysis of Affymetrix GeneChip data at the probe level.

Gautier L, Cope L, Bolstad BM, Irizarry RA.

Bioinformatics. 2004 Feb 12;20(3):307-15.

PMID:
14960456
16.
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18.

Correlating measurements across samples improves accuracy of large-scale expression profile experiments.

Alvarez MJ, Sumazin P, Rajbhandari P, Califano A.

Genome Biol. 2009;10(12):R143. doi: 10.1186/gb-2009-10-12-r143. Epub 2009 Dec 30.

19.

Robust detection and genotyping of single feature polymorphisms from gene expression data.

Wang M, Hu X, Li G, Leach LJ, Potokina E, Druka A, Waugh R, Kearsey MJ, Luo Z.

PLoS Comput Biol. 2009 Mar;5(3):e1000317. doi: 10.1371/journal.pcbi.1000317. Epub 2009 Mar 13.

20.

A statistical framework for the design of microarray experiments and effective detection of differential gene expression.

Zhang SD, Gant TW.

Bioinformatics. 2004 Nov 1;20(16):2821-8. Epub 2004 Jun 4.

PMID:
15180939

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