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Items: 1 to 20 of 110

1.

Optimization of cDNA microarray experimental designs using an evolutionary algorithm.

Gondro C, Kinghorn BP.

IEEE/ACM Trans Comput Biol Bioinform. 2008 Oct-Dec;5(4):630-8. doi: 10.1109/TCBB.2007.70222.

PMID:
18989048
2.

Selection of long oligonucleotides for gene expression microarrays using weighted rank-sum strategy.

Hu G, Llinás M, Li J, Preiser PR, Bozdech Z.

BMC Bioinformatics. 2007 Sep 19;8:350.

3.

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
4.

Statistical designs for two-color spotted microarray experiments.

Chai FS, Liao CT, Tsai SF.

Biom J. 2007 Apr;49(2):259-71.

PMID:
17476948
5.

Evaluation of experimental designs for two-color cDNA microarrays.

Yang CW, Hsiao CF, Chou CK.

J Comput Biol. 2005 Nov;12(9):1202-20.

PMID:
16305329
6.

Reliable classification of two-class cancer data using evolutionary algorithms.

Deb K, Raji Reddy A.

Biosystems. 2003 Nov;72(1-2):111-29.

PMID:
14642662
7.

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
8.

MicroarrayDesigner: an online search tool and repository for near-optimal microarray experimental designs.

Sacan A, Ferhatosmanoglu N, Ferhatosmanoglu H.

BMC Bioinformatics. 2009 Sep 22;10:304. doi: 10.1186/1471-2105-10-304.

9.

Fundamentals of experimental design for cDNA microarrays.

Churchill GA.

Nat Genet. 2002 Dec;32 Suppl:490-5. Review.

PMID:
12454643
10.

ILOOP--a web application for two-channel microarray interwoven loop design.

Pirooznia M, Gong P, Yang JY, Yang MQ, Perkins EJ, Deng Y.

BMC Genomics. 2008 Sep 16;9 Suppl 2:S11. doi: 10.1186/1471-2164-9-S2-S11.

11.

MicroPreP: a cDNA microarray data pre-processing framework.

van Hijum SA, García de la Nava J, Trelles O, Kok J, Kuipers OP.

Appl Bioinformatics. 2003;2(4):241-4.

PMID:
15130795
12.

Measuring differential gene expression by short read sequencing: quantitative comparison to 2-channel gene expression microarrays.

Bloom JS, Khan Z, Kruglyak L, Singh M, Caudy AA.

BMC Genomics. 2009 May 12;10:221. doi: 10.1186/1471-2164-10-221.

13.

Comparison of microarray designs for class comparison and class discovery.

Dobbin K, Simon R.

Bioinformatics. 2002 Nov;18(11):1438-45.

PMID:
12424114
14.
15.

Triple-target microarray experiments: a novel experimental strategy.

Forster T, Costa Y, Roy D, Cooke HJ, Maratou K.

BMC Genomics. 2004 Feb 10;5(1):13.

16.

Highly efficient factorial designs for cDNA microarray experiments: use of approximate theory together with a step-up step-down procedure.

Zhang R, Mukerjee R.

Stat Appl Genet Mol Biol. 2013 Aug;12(4):489-503. doi: 10.1515/sagmb-2012-0054.

PMID:
23813301
17.

A memetic-aided approach to hierarchical clustering from distance matrices: application to gene expression clustering and phylogeny.

Cotta C, Moscato P.

Biosystems. 2003 Nov;72(1-2):75-97. Erratum in: Biosystems. 2004 Nov;77(1-3):229.

PMID:
14642660
18.

In silico gene selection for custom oligonucleotide microarray design.

Sipe CW, Dondeti VR, Saha MS.

Methods Mol Biol. 2007;382:417-28. doi: 10.1007/978-1-59745-304-2_26.

PMID:
18220246
19.

Gene structure-based splice variant deconvolution using a microarray platform.

Wang H, Hubbell E, Hu JS, Mei G, Cline M, Lu G, Clark T, Siani-Rose MA, Ares M, Kulp DC, Haussler D.

Bioinformatics. 2003;19 Suppl 1:i315-22.

PMID:
12855476
20.

Model selection and efficiency testing for normalization of cDNA microarray data.

Futschik M, Crompton T.

Genome Biol. 2004;5(8):R60. Epub 2004 Jul 30.

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