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Items: 1 to 20 of 119

1.

Two-stage normalization using background intensities in cDNA microarray data.

Yoon D, Yi SG, Kim JH, Park T.

BMC Bioinformatics. 2004 Jul 21;5:97.

2.

A robust two-way semi-linear model for normalization of cDNA microarray data.

Wang D, Huang J, Xie H, Manzella L, Soares MB.

BMC Bioinformatics. 2005 Jan 21;6:14.

3.

Evaluation of normalization methods for microarray data.

Park T, Yi SG, Kang SH, Lee S, Lee YS, Simon R.

BMC Bioinformatics. 2003 Sep 2;4:33. Epub 2003 Sep 2.

4.

Optimized LOWESS normalization parameter selection for DNA microarray data.

Berger JA, Hautaniemi S, Järvinen AK, Edgren H, Mitra SK, Astola J.

BMC Bioinformatics. 2004 Dec 9;5:194.

5.

Normalization for two-channel microarray data.

Ittrich C.

Methods Inf Med. 2005;44(3):418-22.

PMID:
16113767
6.

SED, a normalization free method for DNA microarray data analysis.

Wang H, Huang H.

BMC Bioinformatics. 2004 Sep 2;5:121.

7.
8.

A new non-linear normalization method for reducing variability in DNA microarray experiments.

Workman C, Jensen LJ, Jarmer H, Berka R, Gautier L, Nielser HB, Saxild HH, Nielsen C, Brunak S, Knudsen S.

Genome Biol. 2002 Aug 30;3(9):research0048. Epub 2002 Aug 30.

9.

A stepwise framework for the normalization of array CGH data.

Khojasteh M, Lam WL, Ward RK, MacAulay C.

BMC Bioinformatics. 2005 Nov 18;6:274.

11.

Using generalized procrustes analysis (GPA) for normalization of cDNA microarray data.

Xiong H, Zhang D, Martyniuk CJ, Trudeau VL, Xia X.

BMC Bioinformatics. 2008 Jan 16;9:25. doi: 10.1186/1471-2105-9-25.

12.

A robust neural networks approach for spatial and intensity-dependent normalization of cDNA microarray data.

Tarca AL, Cooke JE, Mackay J.

Bioinformatics. 2005 Jun 1;21(11):2674-83. Epub 2005 Mar 29.

PMID:
15797913
13.

Median-of-subsets normalization of intensities for cDNA array data.

Delongchamp RR, Velasco C, Razzaghi M, Harris A, Casciano D.

DNA Cell Biol. 2004 Oct;23(10):653-9.

PMID:
15585123
14.

Evaluation of normalization methods for cDNA microarray data by k-NN classification.

Wu W, Xing EP, Myers C, Mian IS, Bissell MJ.

BMC Bioinformatics. 2005 Jul 26;6:191.

15.

Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, Speed TP.

Nucleic Acids Res. 2002 Feb 15;30(4):e15.

16.

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.

17.

Which is better for cDNA-microarray-based classification: ratios or direct intensities.

Attoor S, Dougherty ER, Chen Y, Bittner ML, Trent JM.

Bioinformatics. 2004 Nov 1;20(16):2513-20. Epub 2004 Sep 28.

PMID:
15454406
18.

Segmentation and intensity estimation of microarray images using a gamma-t mixture model.

Baek J, Son YS, McLachlan GJ.

Bioinformatics. 2007 Feb 15;23(4):458-65. Epub 2006 Dec 12.

PMID:
17166856
19.

Systematic variation normalization in microarray data to get gene expression comparison unbiased.

Chou JW, Paules RS, Bushel PR.

J Bioinform Comput Biol. 2005 Apr;3(2):225-41.

PMID:
15852502
20.

Normalization of cDNA microarray data using wavelet regressions.

Wang J, Ma JZ, Li MD.

Comb Chem High Throughput Screen. 2004 Dec;7(8):783-91.

PMID:
15578940

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