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Items: 1 to 20 of 100

1.

Missing channels in two-colour microarray experiments: combining single-channel and two-channel data.

Lynch AG, Neal DE, Kelly JD, Burtt GJ, Thorne NP.

BMC Bioinformatics. 2007 Jan 25;8:26.

2.
3.

Dimension reduction-based penalized logistic regression for cancer classification using microarray data.

Shen L, Tan EC.

IEEE/ACM Trans Comput Biol Bioinform. 2005 Apr-Jun;2(2):166-75.

PMID:
17044181
4.

Regularized binormal ROC method in disease classification using microarray data.

Ma S, Song X, Huang J.

BMC Bioinformatics. 2006 May 9;7:253.

5.

Eigengene-based linear discriminant model for tumor classification using gene expression microarray data.

Shen R, Ghosh D, Chinnaiyan A, Meng Z.

Bioinformatics. 2006 Nov 1;22(21):2635-42. Epub 2006 Aug 22.

PMID:
16926220
6.

Dimension reduction with redundant gene elimination for tumor classification.

Zeng XQ, Li GZ, Yang JY, Yang MQ, Wu GF.

BMC Bioinformatics. 2008 May 28;9 Suppl 6:S8. doi: 10.1186/1471-2105-9-S6-S8.

7.

Effects of replacing the unreliable cDNA microarray measurements on the disease classification based on gene expression profiles and functional modules.

Wang D, Lv Y, Guo Z, Li X, Li Y, Zhu J, Yang D, Xu J, Wang C, Rao S, Yang B.

Bioinformatics. 2006 Dec 1;22(23):2883-9. Epub 2006 Jun 29.

PMID:
16809389
8.

Stratification bias in low signal microarray studies.

Parker BJ, Günter S, Bedo J.

BMC Bioinformatics. 2007 Sep 2;8:326.

9.

DNA microarrays.

Hofman P.

Nephron Physiol. 2005;99(3):p85-9. Epub 2005 Feb 7. Review.

PMID:
15703470
10.

Microarray based diagnosis profits from better documentation of gene expression signatures.

Kostka D, Spang R.

PLoS Comput Biol. 2008 Feb;4(2):e22. doi: 10.1371/journal.pcbi.0040022.

11.

Expression ratio evaluation in two-colour microarray experiments is significantly improved by correcting image misalignment.

Tang T, François N, Glatigny A, Agier N, Mucchielli MH, Aggerbeck L, Delacroix H.

Bioinformatics. 2007 Oct 15;23(20):2686-91. Epub 2007 Aug 12.

PMID:
17698492
12.

Supervised group Lasso with applications to microarray data analysis.

Ma S, Song X, Huang J.

BMC Bioinformatics. 2007 Feb 22;8:60.

13.

Merging microarray data from separate breast cancer studies provides a robust prognostic test.

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

BMC Bioinformatics. 2008 Feb 27;9:125. doi: 10.1186/1471-2105-9-125.

14.

Simulation study of ratio calculation formulae of two-colour cDNA microarray data.

Jia H, Lu L, Hng SC, Li J.

Appl Bioinformatics. 2006;5(4):255-66.

PMID:
17140272
15.

Robust and accurate cancer classification with gene expression profiling.

Li H, Zhang K, Jiang T.

Proc IEEE Comput Syst Bioinform Conf. 2005:310-21.

PMID:
16447988
16.

Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data.

Zhang C, Li P, Rajendran A, Deng Y, Chen D.

BMC Bioinformatics. 2006 Dec 12;7 Suppl 4:S15.

17.

Smoothing blemished gene expression microarray data via missing value imputation.

Cai Z, Shi Y, Song M, Goebel R, Lin G.

Conf Proc IEEE Eng Med Biol Soc. 2008;2008:5688-91. doi: 10.1109/IEMBS.2008.4650505.

PMID:
19164008
18.

A comparison of background correction methods for two-colour microarrays.

Ritchie ME, Silver J, Oshlack A, Holmes M, Diyagama D, Holloway A, Smyth GK.

Bioinformatics. 2007 Oct 15;23(20):2700-7. Epub 2007 Aug 25.

PMID:
17720982
19.

caCORRECT2: Improving the accuracy and reliability of microarray data in the presence of artifacts.

Moffitt RA, Yin-Goen Q, Stokes TH, Parry RM, Torrance JH, Phan JH, Young AN, Wang MD.

BMC Bioinformatics. 2011 Sep 29;12:383. doi: 10.1186/1471-2105-12-383.

20.

Response projected clustering for direct association with physiological and clinical response data.

Yi SG, Park T, Lee JK.

BMC Bioinformatics. 2008 Jan 31;9:76. doi: 10.1186/1471-2105-9-76.

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