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
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;
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
DOI :
10.1109/CEC.2010.5586494