A novel feature selection scheme for high-dimensional data sets: four-Staged Feature Selection

References

• U. Alon, N. Barkai, D.A. Notterman, K. Gish, S. Ybarra, D. Mack, and A.J. Levine, Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by Oligonucleotide arrays, Proc. Nat. Acad. Sci. U.S.A. 96 (1999), pp. 6745–6750. doi: 10.1073/pnas.96.12.6745
   PubMed Web of Science ®Google Scholar
• C. Ambroise and G.J. McLachlan, Selection bias in gene extraction on the basis of microarray gene-expression data, Proc. Nat. Acad. Sci. U.S.A. 99 (2002), pp. 6562–6566. doi: 10.1073/pnas.102102699
   PubMed Web of Science ®Google Scholar
• P. Baldi and A. Long, A Bayesian framework for the analysis of microarray expression data: Regularized t-test and statistical inferences of gene changes, Bioinformatics 17 (2001), pp. 509–519. doi: 10.1093/bioinformatics/17.6.509
   PubMed Web of Science ®Google Scholar
• V. Bolon-Canedo, N. Sanchez-Marono, and A. Alonso-Betanzos, An ensemble of filters and classifiers for microarray data classification, Pattern Recogn. 45 (2011), pp. 531–539. doi: 10.1016/j.patcog.2011.06.006
   Web of Science ®Google Scholar
• B. Chandra and M. Gupta, An efficient statistical feature selection approach for classification of gene expression data, J. Biomed. Inform. 44 (2011), pp. 529–535. doi: 10.1016/j.jbi.2011.01.001
   PubMed Web of Science ®Google Scholar
• R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification, 2nd ed., John Wiley and Sons, New York, 2001.
   Google Scholar
• T.R. Golub, D.K. Slonim, P. Tamayo, C. Huard, M. Gaasenbeek, J.P. Mesirov, H. Coller, M.L. Loh, J.R. Downing, M.A. Caligiuri, C.D. Bloomfield, and E.S. Lander, Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring, J. Sci. 286 (1999), pp. 531–537. doi: 10.1126/science.286.5439.531
   PubMed Web of Science ®Google Scholar
• G.J. Gordon, R.V. Jensen, L.L. Hsiao, S.R. Gullans, J.E. Blumenstock, S. Ramaswamy, W.G. Richards, D.J. Sugarbaker, and R. Bueno, Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and Mesothelioma, Cancer Res. 62 (2002), pp. 4963–4967.
   PubMed Web of Science ®Google Scholar
• I. Guyon, S. Gunn, M. Nikravesh, and L. Zadeh, Feature Extraction. Foundations and Applications, Springer, New York, 2006.
   Google Scholar
• W. Härdle and L. Simar, Applied Multivariate Statistical Analysis, Springer-Verlag, Berlin Heidelberg, 2007.
   Google Scholar
• S. Haykin, Neural Networks and Learning Machines, Pearson, Upper Saddle River, NJ, 2009.
   Google Scholar
• P. Jafari and F. Azuaje, An assessment of recently published gene expression data analyses: Reporting experimental design and statistical factors, BMC Med. Inform. Decis. Making 6 (2006), p. 27. doi: 10.1186/1472-6947-6-27
   PubMedGoogle Scholar
• K. Kira and L.A. Rendell, A Practical Approach to Feature Selection. Proceedings of the 9th International Conference on Machine Learning, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1992, pp. 249–256.
   Google Scholar
• I. Kononenk, Estimating Features: Analysis and Extension of RELIEF. Proceedings of the 6th European Conference on Machine Learning, Springer-Verlag New York, Inc., Secaucus, NJ, 1994, pp. 171–182.
   Google Scholar
• C. Lee and Y. Leu, A novel hybrid feature selection method for microarray data analysis, Appl. Soft Comput. 11 (2011), pp. 208–213. doi: 10.1016/j.asoc.2009.11.010
   Web of Science ®Google Scholar
• L. Li, T.A. Darden, C.R. Weinberg, A.J. Levine, and L.G. Pedersen, Gene assessment and sample classification for gene expression data using a genetic algorithm/ k-nearest neighbour method, Comb. Chem. High T. Scr. 4 (2001), pp. 727–739.
   PubMed Web of Science ®Google Scholar
• Q. Li, A. Bender, J. Pei, and L. Lai, A large descriptor set and a probabilistic kernel-based classifier significantly improve druglikeness classification, J. Chem. Inf. Model. 47 (2007), pp. 1776–1786. doi: 10.1021/ci700107y
   PubMed Web of Science ®Google Scholar
• T.P. Lu, M.H. Tsai, J.M. Lee, C.P. Hsu, P.C. Chen, C.W. Lin, J.Y. Shih, P.C. Yang, C.K. Hsiao, L.C. Lai, and E.Y. Chuang, Identification of a novel biomarker, SEMA5A, for non-small cell lung carcinoma in nonsmoking women, Cancer Epidem. Biomar. 19 (2010), pp. 2590–2597. doi: 10.1158/1055-9965.EPI-10-0332
   PubMed Web of Science ®Google Scholar
• NCBI, Gene Expression Omnibus Dataset Browser (GEO Dataset Browser). Available at http://www.ncbi.nlm.nih.gov/sites/GDSbrowser/ (Accessed June 2013)
   Google Scholar
• E.F. Petricoin, A.M. Ardekani, B.A. Hitt, P.J. Levine, V.A. Fusaro, S.M. Steinberg, G.B. Mills, C. Simone, D.A. Fishman, E.C. Kohn, and L.A. Liotta, Use of proteomic patterns in serum to identify ovarian cancer, Lancet 359 (2002), pp. 572–577. doi: 10.1016/S0140-6736(02)07746-2
   PubMed Web of Science ®Google Scholar
• S.L. Pomeroy, P. Tamayo, M. Gaasenbeek, L.M. Sturla, M. Angelo, M.E. McLaughlin, J.Y.H. Kim, L.C. Goumnerova, P.M. Black, C. Lau, J.C. Allen, D. Zagzag, J.M. Olson, T. Curran, C. Wetmore, J.A. Biegel, T.P., S. Mukherjee, R. Rifkin, A. Califano, G. Stolovitzky, D.N. Louis, J.P. Mesirov, E.S. Lander, and T.R. Golub, Prediction of central nervous system embryonal tumour outcome based on gene expression, Lett. Nature. 415 (2002), pp. 436–442. doi: 10.1038/415436a
   PubMed Web of Science ®Google Scholar
• C.R. Rao, Linear Statistical Inference and its Application, John Wiley and Sons, New York, 1965.
   Google Scholar
• K. Ridge, Kent Ridge Bio-Medical Dataset. Available at http://levis.tongji.edu.cn/gzli/data/mirror-kentridge.html (Accessed May 2012).
   Google Scholar
• M. Robnik-Sikonja and I. Kononenko, Theoretical and empirical analysis of relief and rReliefF, Mach. Learn. J. 53 (2003), pp. 23–69. doi: 10.1023/A:1025667309714
   Web of Science ®Google Scholar
• R. Ruiz, J.C. Riquelme, and J.S. Aguliar-Ruiz, Incremental wrapper-based gene selection from microarray data for cancer classification, J. Pattern Recogn. 39 (2006), pp. 2383–2392. doi: 10.1016/j.patcog.2005.11.001
   Web of Science ®Google Scholar
• Y. Saeys, I. Inza, and P. Larranaga, A review of feature selection techniques in bioinformatics, Bioinformatics 23 (2007), pp. 2507–2517. doi: 10.1093/bioinformatics/btm344
   PubMed Web of Science ®Google Scholar
• D. Singh, P.G. Febbo, K. Ross, D.G. Jackson, J. Manola, C. Ladd, P. Tamayo, A.A. Renshaw, A.V. D'Amico, J.P. Richie, E.S. Lander, M. Loda, P.W. Kantoff, T.R. Golub, and W.R. Sellers, Gene expression correlates of clinical prostate cancer behavior, Cancer Cell 1 (2002), pp. 203–209. doi: 10.1016/S1535-6108(02)00030-2
   PubMed Web of Science ®Google Scholar
• E. Tian, F. Zhan, R. Walker, E. Rasmussen, Y. Ma, B. Barlogie, and J.D. Jr Shaughnessy, The role of the Wnt-signaling antagonist DKK1 in the development of osteolytic lesions in multiple myeloma, N. Engl. J. Med. 349 (2003), pp. 2483–2494. doi: 10.1056/NEJMoa030847
   PubMed Web of Science ®Google Scholar
• V. Vapnik, The Nature of Statistical Learning Theory, Springer, New York, 1995.
   Google Scholar
• L. Xu, S.S. Shen, Y. Hoshida, A. Subramanian, K. Ross, J.P. Brunet, S.N. Wagner, S. Ramaswamy, J.P. Mesirov, and R.O. Hynes. Gene expression changes in an animal melanoma model correlate with aggressiveness of human melanoma metastases, Mol. Cancer Res. 6 (2008), pp. 760–769. doi: 10.1158/1541-7786.MCR-07-0344
   PubMed Web of Science ®Google Scholar
• Z.R. Yang, R. Thomson, P. McNeil, and R.M. Esnouf, RONN: The Bio-basis function neural network technique applied to the detection of natively disordered regions in proteins, Bioinformatics 21 (2005), pp. 3369–3376. doi: 10.1093/bioinformatics/bti534
   PubMed Web of Science ®Google Scholar
• G. Zhang, A. Schetter, P. He, N. Funamizu, J. Gaedcke, B.M. Ghadimi, T. Ried, R. Hassan, H.G. Yfantis, D.H. Lee, C. Lacy, A. Maitra, N. Hanna, H.R. Alexander, and S.P. Hussain, DPEP1 inhibits tumor cell invasiveness, enhances chemosensitivity and predicts clinical outcome in pancreatic ductal adenocarcinoma, PLoS One. 7 (2012), e31507. doi: 10.1371/journal.pone.0031507
   PubMed Web of Science ®Google Scholar