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

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.

• Type: Journal
• Year: 2010
• Where: CEC
• Authors: Michael A. Lones, Stephen L. Smith, Andrew T. Harris, Alec S. High, Sheila E. Fisher, D. Alastair Smith, Jennifer Kirkham
• Keywords: Artificial Intelligence, CEC 2010, Cell Biochemistry, Context Representation, Output Values