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“Relationship between zinc and the growth and development of young children”, vol. 14, pp. 9730-9738, 2015.
, “Multiclass microarray data classification based on confidence evaluation”, vol. 11. pp. 1357-1369, 2012.
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PMid:10359783 PMCid:21986
Armstrong SA, Staunton JE, Silverman LB, Pieters R, et al. (2002). MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia. Nat. Genet. 30: 41-47.
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http://dx.doi.org/10.1016/j.compbiomed.2007.04.001
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Berrar D, Bradbury I and Dubitzky W (2006). Instance-based concept learning from multiclass DNA microarray data. BMC Bioinformatics 7: 73.
http://dx.doi.org/10.1186/1471-2105-7-73
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Chen YH and Zhao YO (2008). A novel ensemble of classifiers for microarray data classification. Appl. Soft Comp. 8: 1664-1669. 1369
Genetics and Molecular Research 11 (2): 1357-1369 (2012) ©FUNPEC-RP www.funpecrp.com.br
Multiclass classification based on confidence evaluation Debnath R and Kurita T (2010). An evolutionary approach for gene selection and classification of microarray data based on SVM error-bound theories. Biosystems 100: 39-46.
Dougherty ER (2001). Small sample issues for microarray-based classification. Comp. Funct. Genomics 2: 28-34.
http://dx.doi.org/10.1002/cfg.62
PMid:18628896 PMCid:2447190
Evans WE and Guy RK (2004). Gene expression as a drug discovery tool. Nat. Genet. 36: 214-215.
http://dx.doi.org/10.1038/ng0304-214
PMid:14988717
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http://dx.doi.org/10.1093/bioinformatics/16.10.906
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http://dx.doi.org/10.1126/science.286.5439.531
PMid:10521349
Guypn I, Weston J, Barnhill S and Vapnik V (2002). Gene selection for cancer classification using support vector machines. Mach. Learn. 46: 389-422.
http://dx.doi.org/10.1023/A:1012487302797
Horng JT, Wu LC, Liu BJ and Kuo JL (2009). An expert system to classify microarray gene expression data using gene selection by decision tree. Expert. Syst. Appl. 36: 9072-9081.
http://dx.doi.org/10.1016/j.eswa.2008.12.037
Inza I, Larranaga P, Blanco R and Cerrolaza AJ (2004). Filter versus wrapper gene selection approaches in DNA microarray domains. Artif. Intell. Med. 31: 91-103.
http://dx.doi.org/10.1016/j.artmed.2004.01.007
PMid:15219288
Khan J, Wei JS, Ringner M, Saal LH, et al. (2001). Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat. Med. 7: 673-679.
http://dx.doi.org/10.1038/89044
PMid:11385503 PMCid:1282521
Kim KJ and Cho SB (2008). An evolutionary algorithm approach to optimal ensemble classifiers for DNA microarray data analysis. IEEE Trans. Evol. Comput. 12: 377-388.
http://dx.doi.org/10.1109/TEVC.2007.906660
Lee YK and Lee C-K (2003). Classification of multiple cancer types by multicategory support vector machines using gene expression data. Bioinformatics 19: 1132-1139.
http://dx.doi.org/10.1093/bioinformatics/btg102
PMid:12801874
Li LP, Weinberg CR, Darden TA and Pedersen LG (2001). Gene selection for sample classification based on gene expression data: study of sensitivity to choice of parameters of the GA/KNN method. Bioinformatics 17: 1131-1142.
http://dx.doi.org/10.1093/bioinformatics/17.12.1131
PMid:11751221
Li T, Zhang CL and Ogihara M (2004). A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression. Bioinformatics 20: 2429-2437.
http://dx.doi.org/10.1093/bioinformatics/bth267
PMid:15087314
Nutt CL, Mani DR, Betensky RA, Tamayo P, et al. (2003). Gene expression-based classification of malignant gliomas correlates better with survival than histological classification. Cancer Res. 63: 1602-1607.
PMid:12670911
Pomeroy SL, Tamayo P, Gaasenbeek M and Sturla LM (2002). Prediction of central nervous system embryonal tumour outcome based on gene expression. Nature 415: 436-442.
http://dx.doi.org/10.1038/415436a
PMid:11807556
Shen L and Tan EC (2006). Reducing multiclass cancer classification to binary by output coding and SVM. Comput. Biol. Chem. 30: 63-71.
http://dx.doi.org/10.1016/j.compbiolchem.2005.10.008
PMid:16321568
Statnikov A, Aliferis CF, Tsamardinos I, Hardin D, et al. (2005). A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis. Bioinformatics 21: 631-643.
http://dx.doi.org/10.1093/bioinformatics/bti033
PMid:15374862
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Tan Y, Shi L, Tong W, Hwang GT, et al. (2004). Multi-class tumor classification by discriminant partial least squares using microarray gene expression data and assessment of classification models. Comput. Biol. Chem. 28: 235-244.
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Yu HL, Gu GC, Liu HB and Shen J (2010). Feature subspace ensemble classifiers for microarray data. ICIC Express Lett. 4: 143-147.