Baldi, P. and Long, A. (2001). A Bayesian framework for the analysis of microarray expression data: Regularized t-test and statistical inference of gene changes, Bioinformatics 17(4): 509-519.10.1093/bioinformatics/17.6.50911395427
Chang, C.-C. and Lin, C.-J. (2011). LibSVM: A library for support vector machines, ACM Transactions on Intelligent Systems and Technology 1(27): 1-27.10.1145/1961189.1961199
Eisen, M., Spellman, P. and Brown, P. (1998). Cluster analysis and display of genome wide expression patterns, Proceedings of the National Academy of Sciences 95(25): 14863-14868.10.1073/pnas.95.25.14863245419843981
Fan, R.-E., Chen, P.-H. and Lin, C.-J. (2005). Working set selection using second order information for training SVM, Journal of Machine Learning Research 6(12): 1889-1918.
Furey, T., Cristianini, N., Duffy, N., Bednarski, D., Schummer, M. and Haussler, D. (2000). Support vector machine classification and validation of cancer tissue samples using microarray expression data, Bioinformatics 16(10): 906-914.10.1093/bioinformatics/16.10.90611120680
Golub, T., Slonim, D.K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J.P., Coller, H., Loh, M.L., Downing, J.R., Caligiuri, M.A. and Bloomfield, C.D. (1999). Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring, Science 286(5439): 531-537.10.1126/science.286.5439.53110521349
Guyon, I., Weston, A., Barnhill, S. and Vapnik, V. (2002). Gene selection for cancer classification using SVM, Machine Learning 46(1-3): 389-422.10.1023/A:1012487302797
Herrero, J., Valencia, A. and Dopazon, A. (2001). A hierarchical unsupervised growing neural network for clustering gene expression patterns, Bioinformatics 17(2): 126-136.10.1093/bioinformatics/17.2.12611238068
Hewett, R. and Kijsanayothin, P. (2008). Tumor classification ranking from microarray data, BMC Genomics 9(2): 1-11.10.1186/1471-2164-9-S2-S21255988618831787
Huang, T.M. and Kecman, V. (2005). Gene extraction for cancer diagnosis by support vector machines-an improvement, Artificial Intelligence in Medicine 9(35): 185-194.10.1016/j.artmed.2005.01.00616026974
Huang, X. and Pan, W. (2003). Linear regression and two-class classification with gene expression data, Bioinformatics 19(16): 2072-2078.10.1093/bioinformatics/btg28314594712
Makinaci, M. (2007). Support vector machine approach for classification of cancerous prostate regions, World Academy of Science, Engineering and Technology 1(7): 166-169.
Mitsubayashi, H., Aso, S., Nagashima, T. and Okada, Y. (2008). Accurate and robust gene selection for desease classification using a simple statistics, Biomedical Informatics 3(2): 68-71.10.6026/97320630003068263795419238233
Ramaswamy, S., Tamayo, P., Rifkin, R., Mukherjee, S., Yeang, C., Angelo, M., Ladd, C., Reich, M., Latulippe, E., Mesirov, J., Poggio, T., Gerald, W., Loda, M., Lander, E. and Golub, T. (2001). Multiclass cancer diagnosis using tumor gene expression signatures, Proceedings of the National Academy of Sciences 98(26): 15149-15154.10.1073/pnas.2115663986499811742071
Sabo, K. (2014). Center-based l1-clustering method, International Journal of Applied Mathematics and Computer Science 24(1): 151-163, DOI: 10.2478/amcs-2014-0012.10.2478/amcs-2014-0012
Sprent, P. and Smeeton, N. (2007). Applied Nonparametric Statistical Methods, Chapman and Hall-CRC, Boca Raton, FL. ´S winiarski, R.W. (2001). Rough sets methods in feature reduction and classification, International Journal of Applied Mathematics and Computer Science 11(3): 565-582.
Vert, J. (2007). Kernel methods in genomics and computational biology, in G. Camps-Valls, J.L. Rojo-Alvarez and M. Martinez-Ramon (Eds.), Kernel Methods in Bioengineering, Signal and Image Processing, Idea Group, London, pp. 42-64.10.4018/978-1-59904-042-4.ch002
Wang, X. and Gotoh, O. (2010). A robust gene selection method for microarray-based cancer classification, Cancer Informatics 9(2): 15-30.10.4137/CIN.S3794283437720234770
Wiliński, A. and Osowski, S. (2012). Ensemble of data mining methods for gene ranking, Bulletin of the Polish Academy of Sciences 60(3): 461-471.10.2478/v10175-012-0058-x
Woolf, P.J. and Wang, Y. (2000). A fuzzy logic approach to analyzing gene expression data, Physiological Genomics 3(1): 9-15.10.1152/physiolgenomics.2000.3.1.911015595
Yang, F. (2011). Robust feature selection for microarray data based on multicriterion fusion, IEEE Transactions on Computational Biology and Bioinformatics 8(4): 1080-1092. 10.1109/TCBB.2010.10321566255