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
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