THE FEATURE EXTRACTION AND CLASSIFICATION OF MATERNAL CIGARETTE-SMOKING SIGNATURES BY EUCLIDEAN DISTANCE METHOD AND ALTERNATIVE NEURAL NETWORKS

Tuğba Saatçı-Ayten , Umut Engin Ayten, Oğuzhan Yavuz, Lale Özyılmaz

References

  1. [1] 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: Classdiscovery and class prediction by gene expressionmonitoring, Science, 286, 1999, 531-537.
  2. [2] A. Spira, J. Beane, V. Pinto-Plata, A. Kadar, G. Liu,V. Shah, B. Celli, J. S. Brody, Gene Expression Profilingof Human Lung Tissue from Smokers with SevereEmphysema, American Journal of Respiratory Cell andMolecular Biology, 31, 2004, 601-610.
  3. [3] P. Huuskonen, M. Storvik, M. Reinisalo, P.Honkakoski, J. Rysa, M. Pasanen, Microarray analysis ofthe global alterations in the gene expression in theplacentas from cigarette-smoking mothers, ClinicalPharmacology & Therapeutics, 83, 2008, 542-550.
  4. [4] C. Bi, C. Vyhlidal, S. Leeder, Supervised Learningof Maternal Cigarette-Smoking Signatures from PlacentalGene Expression Data: A Case Study. Proc. IEEEComputational Intelligence Symposium on Bioinformatics& Computational Biology (CIBCB), Montreal, Canada,2010, 1-6.
  5. [5] T. S. Furey, T. S. Cristianini, N. Duffy, D. W.Bednarski, M. Schummer, and D. Haussler, Supportvector machine classification and validation of cancertissue samples using microarray expression data,Bioinformatics, 16, 2001, 906-914.
  6. [6] C. Bi, M. C. Saunders, and B. A. McPheron, Wingpattern-based classification of the Rhagoletis pomonellaspecies complex using genetic neural networks, Int. J.Computer Sci & Appl., 4, 2007, 1-14.
  7. [7] E. Deza, M. M. Deza, Encyclopedia of Distances(Springer, 2009, 94).
  8. [8] I. Aleksander, I. Morton, An introduction to neuralcomputing (International Thomson Computer Press,1995).
  9. [9] W. S. McCulloch, and W. H. Pitts, A logical calculusof the ideas immanent in nervous activity, Bulletin ofMathematical Biophysics, 5, 1943, 115-133.
  10. [10] J. S. R. Jang, C. T. Sun, E. Mizutani, Neuro-Fuzzyand Soft Computing (Prentice Hall, USA, 1997).
  11. [11] A. B. Gardner, A. M. Krieger, G. Vachtsevanos, andB. Litt, One-Class Novelty Detection for Seizure Analysisfrom Intracranial EEG, Journal of Machine LearningResearch, 7, 2006, 1025-1044.
  12. [12] V. N. Vapnik, Statistical Learning Theory (JohnWiley and Sons, New York, 1998).
  13. [13] V. N. Vapnik, The Nature of Statistical LearningTheory (Springer-Verlag, New York, 1999).568

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