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Items: 1 to 20 of 54

1.

Classifying gene expression profiles from pairwise mRNA comparisons.

Geman D, d'Avignon C, Naiman DQ, Winslow RL.

Stat Appl Genet Mol Biol. 2004;3:Article19. Epub 2004 Aug 30.

2.

Simple decision rules for classifying human cancers from gene expression profiles.

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

Bioinformatics. 2005 Oct 15;21(20):3896-904. Epub 2005 Aug 16.

3.

Pairwise protein expression classifier for candidate biomarker discovery for early detection of human disease prognosis.

Kaur P, Schlatzer D, Cooke K, Chance MR.

BMC Bioinformatics. 2012 Aug 7;13:191. doi: 10.1186/1471-2105-13-191.

4.

A new method for class prediction based on signed-rank algorithms applied to Affymetrix microarray experiments.

Rème T, Hose D, De Vos J, Vassal A, Poulain PO, Pantesco V, Goldschmidt H, Klein B.

BMC Bioinformatics. 2008 Jan 11;9:16. doi: 10.1186/1471-2105-9-16.

5.

Safety and nutritional assessment of GM plants and derived food and feed: the role of animal feeding trials.

EFSA GMO Panel Working Group on Animal Feeding Trials.

Food Chem Toxicol. 2008 Mar;46 Suppl 1:S2-70. doi: 10.1016/j.fct.2008.02.008. Epub 2008 Feb 13. Review.

PMID:
18328408
6.

Accurate cancer classification using expressions of very few genes.

Wang L, Chu F, Xie W.

IEEE/ACM Trans Comput Biol Bioinform. 2007 Jan-Mar;4(1):40-53.

PMID:
17277412
7.

Appropriateness of some resampling-based inference procedures for assessing performance of prognostic classifiers derived from microarray data.

Lusa L, McShane LM, Radmacher MD, Shih JH, Wright GW, Simon R.

Stat Med. 2007 Feb 28;26(5):1102-13.

PMID:
16755534
9.
11.
12.

Relative expression analysis for molecular cancer diagnosis and prognosis.

Eddy JA, Sung J, Geman D, Price ND.

Technol Cancer Res Treat. 2010 Apr;9(2):149-59. Review.

13.

SlimPLS: a method for feature selection in gene expression-based disease classification.

Gutkin M, Shamir R, Dror G.

PLoS One. 2009 Jul 29;4(7):e6416. doi: 10.1371/journal.pone.0006416.

14.

The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer.

Mitra AP, Almal AA, George B, Fry DW, Lenehan PF, Pagliarulo V, Cote RJ, Datar RH, Worzel WP.

BMC Cancer. 2006 Jun 16;6:159.

15.

Gene expression profiling in uveal melanoma: two regions on 3p related to prognosis.

van Gils W, Lodder EM, Mensink HW, Kiliç E, Naus NC, Brüggenwirth HT, van Ijcken W, Paridaens D, Luyten GP, de Klein A.

Invest Ophthalmol Vis Sci. 2008 Oct;49(10):4254-62. doi: 10.1167/iovs.08-2033. Epub 2008 Jun 14.

PMID:
18552379
16.

Gene selection for classification of microarray data based on the Bayes error.

Zhang JG, Deng HW.

BMC Bioinformatics. 2007 Oct 3;8(1):370.

17.

A new classification model with simple decision rule for discovering optimal feature gene pairs.

Li J, Tang X.

Comput Biol Med. 2007 Nov;37(11):1637-46. Epub 2007 May 7.

PMID:
17482157
18.

[Development of antituberculous drugs: current status and future prospects].

Tomioka H, Namba K.

Kekkaku. 2006 Dec;81(12):753-74. Review. Japanese.

PMID:
17240921
19.

SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition.

Melvin I, Ie E, Kuang R, Weston J, Stafford WN, Leslie C.

BMC Bioinformatics. 2007 May 22;8 Suppl 4:S2.

20.

Gene expression profile class prediction using linear Bayesian classifiers.

Asyali MH.

Comput Biol Med. 2007 Dec;37(12):1690-9. Epub 2007 May 22.

PMID:
17517385
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