Novel Extension of k - TSP Algorithm for Microarray Classification

Authors:
Marcin Czajkowski;Marek Krętowski
Affiliations:
Faculty of Computer Science, Białystok Technical University, Białystok, Poland 15-351;Faculty of Computer Science, Białystok Technical University, Białystok, Poland 15-351
Venue:
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Year:
2008

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Abstract

This paper presents a new method, referred as Weightk茂戮驴 TSP, which generates simple and accurate decision rules that can be widely used for classifying gene expression data. The proposed method extends previous approaches: TSPand k茂戮驴 TSPalgorithms by considering weight pairwise mRNA comparisons and percentage changes of gene expressions in different classes. Both rankings have been modified as well as decision rules, however the concept of "relative expression reversals" is retained. New solutions to match analyzed datasets more accurately were also included. Experimental validation was performed on several human microarray datasets and obtained results are promising.