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Items: 1 to 20 of 112

1.

Semi-supervised analysis of gene expression profiles for lineage-specific development in the Caenorhabditis elegans embryo.

Qi Y, Missiuro PE, Kapoor A, Hunter CP, Jaakkola TS, Gifford DK, Ge H.

Bioinformatics. 2006 Jul 15;22(14):e417-23.

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Kernel hierarchical gene clustering from microarray expression data.

Qin J, Lewis DP, Noble WS.

Bioinformatics. 2003 Nov 1;19(16):2097-104.

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Biologically supervised hierarchical clustering algorithms for gene expression data.

Boratyn GM, Datta S, Datta S.

Conf Proc IEEE Eng Med Biol Soc. 2006;1:5515-8.

PMID:
17947147
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Combining Pareto-optimal clusters using supervised learning for identifying co-expressed genes.

Maulik U, Mukhopadhyay A, Bandyopadhyay S.

BMC Bioinformatics. 2009 Jan 20;10:27. doi: 10.1186/1471-2105-10-27.

11.

Learning rule-based models of biological process from gene expression time profiles using gene ontology.

Hvidsten TR, Laegreid A, Komorowski J.

Bioinformatics. 2003 Jun 12;19(9):1116-23.

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A mixture model with random-effects components for clustering correlated gene-expression profiles.

Ng SK, McLachlan GJ, Wang K, Ben-Tovim Jones L, Ng SW.

Bioinformatics. 2006 Jul 15;22(14):1745-52.

14.

Identification of lineage-specific zygotic transcripts in early Caenorhabditis elegans embryos.

Robertson SM, Shetty P, Lin R.

Dev Biol. 2004 Dec 15;276(2):493-507.

15.

Context-specific infinite mixtures for clustering gene expression profiles across diverse microarray dataset.

Liu X, Sivaganesan S, Yeung KY, Guo J, Bumgarner RE, Medvedovic M.

Bioinformatics. 2006 Jul 15;22(14):1737-44.

16.

Reliable gene signatures for microarray classification: assessment of stability and performance.

Davis CA, Gerick F, Hintermair V, Friedel CC, Fundel K, Küffner R, Zimmer R.

Bioinformatics. 2006 Oct 1;22(19):2356-63.

17.

A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis.

Statnikov A, Aliferis CF, Tsamardinos I, Hardin D, Levy S.

Bioinformatics. 2005 Mar 1;21(5):631-43.

18.

Gene expression data analysis with a dynamically extended self-organized map that exploits class information.

Mavroudi S, Papadimitriou S, Bezerianos A.

Bioinformatics. 2002 Nov;18(11):1446-53.

20.

Clinically driven semi-supervised class discovery in gene expression data.

Steinfeld I, Navon R, Ardigò D, Zavaroni I, Yakhini Z.

Bioinformatics. 2008 Aug 15;24(16):i90-7. doi: 10.1093/bioinformatics/btn279.

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