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Items: 1 to 20 of 431

1.

Pathway analysis using random forests classification and regression.

Pang H, Lin A, Holford M, Enerson BE, Lu B, Lawton MP, Floyd E, Zhao H.

Bioinformatics. 2006 Aug 15;22(16):2028-36. Epub 2006 Jun 29.

PMID:
16809386
2.

HykGene: a hybrid approach for selecting marker genes for phenotype classification using microarray gene expression data.

Wang Y, Makedon FS, Ford JC, Pearlman J.

Bioinformatics. 2005 Apr 15;21(8):1530-7. Epub 2004 Dec 7.

PMID:
15585531
3.

Robust classification modeling on microarray data using misclassification penalized posterior.

Soukup M, Cho H, Lee JK.

Bioinformatics. 2005 Jun;21 Suppl 1:i423-30.

PMID:
15961487
4.

Pathway recognition and augmentation by computational analysis of microarray expression data.

Novak BA, Jain AN.

Bioinformatics. 2006 Jan 15;22(2):233-41. Epub 2005 Nov 8.

PMID:
16278238
5.

Methods for labeling error detection in microarrays based on the effect of data perturbation on the regression model.

Zhang C, Wu C, Blanzieri E, Zhou Y, Wang Y, Du W, Liang Y.

Bioinformatics. 2009 Oct 15;25(20):2708-14. doi: 10.1093/bioinformatics/btp478. Epub 2009 Aug 6.

PMID:
19661242
7.
8.

Bayesian variable selection for the analysis of microarray data with censored outcomes.

Sha N, Tadesse MG, Vannucci M.

Bioinformatics. 2006 Sep 15;22(18):2262-8. Epub 2006 Jul 15.

PMID:
16845144
9.

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
10.

Classification based upon gene expression data: bias and precision of error rates.

Wood IA, Visscher PM, Mengersen KL.

Bioinformatics. 2007 Jun 1;23(11):1363-70. Epub 2007 Mar 28. Review.

PMID:
17392326
11.
12.

Pathway analysis using random forests with bivariate node-split for survival outcomes.

Pang H, Datta D, Zhao H.

Bioinformatics. 2010 Jan 15;26(2):250-8. doi: 10.1093/bioinformatics/btp640. Epub 2009 Nov 18.

13.

Tumor classification ranking from microarray data.

Hewett R, Kijsanayothin P.

BMC Genomics. 2008 Sep 16;9 Suppl 2:S21. doi: 10.1186/1471-2164-9-S2-S21.

14.

Ensemble gene selection by grouping for microarray data classification.

Liu H, Liu L, Zhang H.

J Biomed Inform. 2010 Feb;43(1):81-7. doi: 10.1016/j.jbi.2009.08.010. Epub 2009 Aug 20.

15.

A framework to identify physiological responses in microarray-based gene expression studies: selection and interpretation of biologically relevant genes.

Rodenburg W, Heidema AG, Boer JM, Bovee-Oudenhoven IM, Feskens EJ, Mariman EC, Keijer J.

Physiol Genomics. 2008 Mar 14;33(1):78-90. Epub 2007 Dec 27.

16.

Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm.

Grotkjaer T, Winther O, Regenberg B, Nielsen J, Hansen LK.

Bioinformatics. 2006 Jan 1;22(1):58-67. Epub 2005 Oct 27.

PMID:
16257984
17.

Bioinformatics analysis of microarray data.

Zhang Y, Szustakowski J, Schinke M.

Methods Mol Biol. 2009;573:259-84. doi: 10.1007/978-1-60761-247-6_15. Review.

PMID:
19763933
18.

Modeling nonlinearity in dilution design microarray data.

Zheng X, Huang HC, Li W, Liu P, Li QZ, Liu Y.

Bioinformatics. 2007 Jun 1;23(11):1339-47. Epub 2007 Jan 19.

PMID:
17237040
19.

Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA.

Nueda MJ, Conesa A, Westerhuis JA, Hoefsloot HC, Smilde AK, Talón M, Ferrer A.

Bioinformatics. 2007 Jul 15;23(14):1792-800. Epub 2007 May 22.

PMID:
17519250
20.

Optimization models for cancer classification: extracting gene interaction information from microarray expression data.

Antonov AV, Tetko IV, Mader MT, Budczies J, Mewes HW.

Bioinformatics. 2004 Mar 22;20(5):644-52. Epub 2004 Jan 22.

PMID:
15033871

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