[1] Chang C.-W., Cheng W.-C., Chen C.-R., Shu W.-Y., Tsai M.-L., et al., Identiﬁcation of Human Housekeeping Genes and Tissue-Selective Genes by Microarray Meta-Analysis. PLoS ONE, 2011, 6(7): e22859, doi:10.1371/journal.pone.0022859.
[2] Dougherty E.R., Hua J., Sima C., Performance of Feature Selection Methods. Curr. Genomics. 2009, 10, pp. 365–374.
[3] Eisenberg E., Levanon E.Y., Human housekeeping genes, revisited. Trends in Genetics, October 2013, 29(10), pp. 569–574, doi:10.1016/j.tig.2013.05.010.
[4] Guyon I., Weston J., Barnhill S., Vapnik V., Gene selection for cancer classiﬁcation using support vector machines. Machine Learning, 2002, 46, pp. 389–422.
[5] Janecek A., Gansterer W., Demel W., Ecker G., On the relationship between feature selection and classiﬁcation accuracy. Journal of Machine Learning and Research, 2008, 4, pp. 90–105.
[6] Kumar A.P., Valsala P., Feature Selection for high Dimensional DNA Microarray data using hybrid approaches. Bioinformation, 2013, 9(16), pp. 824–828.
[7] Li X., Lu H., Wang M., A Hybrid Gene Selection Method for Multi-category Tumor Classiﬁcation using Microarray Data. Int. J. Bioautomation, 2013, 17(4), pp. 249–258.
[8] Li X., Peng S., Zhan X., Zhang J., Xu Y., Comparison of feature selection methods for multiclass cancer classiﬁcation based on microarray data. Proceedings of the 4th International Conference on Biomedical Engineering and Informatics (BMEI), 2011, 3, pp. 1692–1696.
[9] Liu G., Kong L., Gopalakrishnan V., A Partitioning Based Adaptive Method for Robust Removal of Irrelevant Features from High-dimensional Biomedical Datasets. AMIA Summits on Translational Science Proceedings, 2012, pp. 52–61.
[10] Podolak I. T., Roman A., CORES: fusion of supervised and unsupervised training methods for a multi-class classiﬁcation problem. Pattern Analysis and Applications, 2011, 14, pp. 395–413.
[11] Saeys Y., Inaki I., Larranaga P., A review of feature selection techniques in bioinformatics. Bioinformatics, 2007, 23(19), pp. 2507–2517.
[12] S´aez J.A., Luengo J., Stefanowski J., Herrera F., SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classiﬁcation by a resampling method with ﬁltering. Information Sciences, 10 January 2015, 291, pp. 184–203, http://dx.doi.org/10.1016/j.ins.2014.08.051. 
[13] Trevino V., Falciani F., Barrera-Saldana H.A., DNA Microarrays: a Powerful Genomic Tool for Biomedical and Clinical Research. Molecular Medicine, 2007, 13(9–10), pp. 527–541.
[14] Wang X., Gotoh O., A Robust Gene Selection Method for Microarray-based Cancer Classiﬁcation. Cancer Informatics, 2010, 9, pp. 15–30.
[15] Wang Y., Tetko I.V., Hall M.A., Frank E., Facius A., Mayer K.F., Gene selection from microarray data for cancer classiﬁcation–a machine learning approach. Comput. Biol. Chem., 2005, 29, pp. 37–46.
[16] Wo´zniak M., Graa M., Corchado E., A survey of multiple classiﬁer systems as hybrid systems. Information Fusion, 2014, 16, pp. 3–17.
[17] Zhang H., Wang H., Dai Z., Chen M.S., Yuan Z., Improving accuracy for cancer classiﬁcation with a new algorithm for genes selection. BMC Bioinformatics, 2012, 13 (298), pp. 1.
