• DocumentCode
    2333677
  • Title

    Discriminating normal and cancerous thyroid cell lines using implicit context representation Cartesian genetic programming

  • Author

    Lones, Michael A. ; Smith, Stephen L. ; Harris, Andrew T. ; High, Alec S. ; Fisher, Sheila E. ; Smith, D. Alastair ; Kirkham, Jennifer

  • Author_Institution
    Dept. of Electron., Univ. of York, York, UK
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, we describe a method for discriminating between thyroid cell lines. Five commercial thyroid cell lines were obtained, ranging from non-cancerous to cancerous varieties. Raman spectroscopy was used to interrogate native cell biochemistry. Following suitable normalisation of the data, implicit context representation Cartesian genetic programming was then used to search for classifiers capable of distinguishing between the spectral fingerprints of the different cell lines. The results are promising, producing comprehensible classifiers whose output values correlate with biological aggressiveness.
  • Keywords
    Raman spectra; biochemistry; cancer; cellular biophysics; genetic algorithms; medical diagnostic computing; pattern classification; Cartesian genetic programming; Raman spectroscopy; biological aggressiveness; cancerous thyroid cell line; cell biochemistry; implicit context representation; normal thyroid cell line; spectral fingerprint; Cancer; Chemicals; Context; Electronic mail; Genetic programming; Materials;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2010 IEEE Congress on
  • Conference_Location
    Barcelona
  • Print_ISBN
    978-1-4244-6909-3
  • Type

    conf

  • DOI
    10.1109/CEC.2010.5586494
  • Filename
    5586494