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Items: 1 to 20 of 40

1.

Biomarker identification by knowledge-driven multilevel ICA and motif analysis.

Chen L, Xuan J, Wang C, Wang Y, Shih IeM, Wang TL, Zhang Z, Clarke R, Hoffman EP.

Int J Data Min Bioinform. 2009;3(4):365-81.

PMID:
20052902
2.

Knowledge-guided multi-scale independent component analysis for biomarker identification.

Chen L, Xuan J, Wang C, Shih IeM, Wang Y, Zhang Z, Hoffman E, Clarke R.

BMC Bioinformatics. 2008 Oct 6;9:416. doi: 10.1186/1471-2105-9-416.

3.

Functional genomics and proteomics in the clinical neurosciences: data mining and bioinformatics.

Phan JH, Quo CF, Wang MD.

Prog Brain Res. 2006;158:83-108. Review.

PMID:
17027692
4.

Finding dominant sets in microarray data.

Fu X, Teng L, Li Y, Chen W, Mao Y, Shen IF, Xie Y.

Front Biosci. 2005 Sep 1;10:3068-77.

PMID:
15970561
5.

cluML: A markup language for clustering and cluster validity assessment of microarray data.

Bolshakova N, Cunningham P.

Appl Bioinformatics. 2005;4(3):211-3.

PMID:
16231963
6.

Meta-analysis of gene expression data: a predictor-based approach.

Fishel I, Kaufman A, Ruppin E.

Bioinformatics. 2007 Jul 1;23(13):1599-606. Epub 2007 Apr 26.

PMID:
17463023
7.

Signature Evaluation Tool (SET): a Java-based tool to evaluate and visualize the sample discrimination abilities of gene expression signatures.

Jen CH, Yang TP, Tung CY, Su SH, Lin CH, Hsu MT, Wang HW.

BMC Bioinformatics. 2008 Jan 28;9:58. doi: 10.1186/1471-2105-9-58.

8.

A mathematical and computational framework for quantitative comparison and integration of large-scale gene expression data.

Hart CE, Sharenbroich L, Bornstein BJ, Trout D, King B, Mjolsness E, Wold BJ.

Nucleic Acids Res. 2005 May 10;33(8):2580-94. Print 2005.

9.

Use of principal component analysis and the GE-biplot for the graphical exploration of gene expression data.

Pittelkow Y, Wilson SR.

Biometrics. 2005 Jun;61(2):630-2; discussion 632-4.

PMID:
16011715
11.

Multievidence microarray mining.

Seifert M, Scherf M, Epple A, Werner T.

Trends Genet. 2005 Oct;21(10):553-8.

PMID:
16098629
12.

mAPC-GibbsOS: an integrated approach for robust identification of gene regulatory networks.

Shi X, Gu J, Chen X, Shajahan A, Hilakivi-Clarke L, Clarke R, Xuan J.

BMC Syst Biol. 2013;7 Suppl 5:S4. doi: 10.1186/1752-0509-7-S5-S4. Epub 2013 Dec 9.

13.

Clustering microarray gene expression data using weighted Chinese restaurant process.

Qin ZS.

Bioinformatics. 2006 Aug 15;22(16):1988-97. Epub 2006 Jun 9.

PMID:
16766561
15.
16.

CLEAN: CLustering Enrichment ANalysis.

Freudenberg JM, Joshi VK, Hu Z, Medvedovic M.

BMC Bioinformatics. 2009 Jul 29;10:234. doi: 10.1186/1471-2105-10-234.

17.

Gene expression module discovery using gibbs sampling.

Wu CJ, Fu Y, Murali TM, Kasif S.

Genome Inform. 2004;15(1):239-48.

PMID:
15712126
18.

Design and evaluation of Actichip, a thematic microarray for the study of the actin cytoskeleton.

Muller J, Mehlen A, Vetter G, Yatskou M, Muller A, Chalmel F, Poch O, Friederich E, Vallar L.

BMC Genomics. 2007 Aug 29;8:294.

19.

Challenges in projecting clustering results across gene expression-profiling datasets.

Lusa L, McShane LM, Reid JF, De Cecco L, Ambrogi F, Biganzoli E, Gariboldi M, Pierotti MA.

J Natl Cancer Inst. 2007 Nov 21;99(22):1715-23. Epub 2007 Nov 13.

PMID:
18000217
20.

Lung cancer gene expression database analysis incorporating prior knowledge with support vector machine-based classification method.

Guan P, Huang D, He M, Zhou B.

J Exp Clin Cancer Res. 2009 Jul 18;28:103. doi: 10.1186/1756-9966-28-103.

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