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Items: 1 to 20 of 109

1.

iPcc: a novel feature extraction method for accurate disease class discovery and prediction.

Ren X, Wang Y, Zhang XS, Jin Q.

Nucleic Acids Res. 2013 Aug;41(14):e143. doi: 10.1093/nar/gkt343. Epub 2013 Jun 12.

2.

A unified computational model for revealing and predicting subtle subtypes of cancers.

Ren X, Wang Y, Wang J, Zhang XS.

BMC Bioinformatics. 2012 May 1;13:70. doi: 10.1186/1471-2105-13-70.

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Optimization based tumor classification from microarray gene expression data.

Dagliyan O, Uney-Yuksektepe F, Kavakli IH, Turkay M.

PLoS One. 2011 Feb 4;6(2):e14579. doi: 10.1371/journal.pone.0014579.

5.

Reliable classification of two-class cancer data using evolutionary algorithms.

Deb K, Raji Reddy A.

Biosystems. 2003 Nov;72(1-2):111-29.

PMID:
14642662
6.

Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework.

Yang L, Ainali C, Tsoka S, Papageorgiou LG.

BMC Bioinformatics. 2014 Dec 5;15:390. doi: 10.1186/s12859-014-0390-2.

7.

Simultaneous gene clustering and subset selection for sample classification via MDL.

Jörnsten R, Yu B.

Bioinformatics. 2003 Jun 12;19(9):1100-9.

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New algorithms for multi-class cancer diagnosis using tumor gene expression signatures.

Bagirov AM, Ferguson B, Ivkovic S, Saunders G, Yearwood J.

Bioinformatics. 2003 Sep 22;19(14):1800-7.

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11.

SC(3): Triple spectral clustering-based consensus clustering framework for class discovery from cancer gene expression profiles.

Zhiwen Y, Le L, Jane Y, Hau-San W, Guoqiang H.

IEEE/ACM Trans Comput Biol Bioinform. 2012 Nov-Dec;9(6):1751-65.

PMID:
22868680
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13.

Bagging to improve the accuracy of a clustering procedure.

Dudoit S, Fridlyand J.

Bioinformatics. 2003 Jun 12;19(9):1090-9.

14.

Cancer classification from the gene expression profiles by Discriminant Kernel-PLS.

Tang KL, Yao WJ, Li TH, Li YX, Cao ZW.

J Bioinform Comput Biol. 2010 Dec;8 Suppl 1:147-60.

PMID:
21155025
15.

Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery.

Han H, Li XL.

BMC Bioinformatics. 2011 Feb 15;12 Suppl 1:S7. doi: 10.1186/1471-2105-12-S1-S7.

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Recursive cluster elimination (RCE) for classification and feature selection from gene expression data.

Yousef M, Jung S, Showe LC, Showe MK.

BMC Bioinformatics. 2007 May 2;8:144.

19.

A multi-class predictor based on a probabilistic model: application to gene expression profiling-based diagnosis of thyroid tumors.

Yukinawa N, Oba S, Kato K, Taniguchi K, Iwao-Koizumi K, Tamaki Y, Noguchi S, Ishii S.

BMC Genomics. 2006 Jul 27;7:190.

20.

Marker identification and classification of cancer types using gene expression data and SIMCA.

Bicciato S, Luchini A, Di Bello C.

Methods Inf Med. 2004;43(1):4-8.

PMID:
15026826
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