Gene selection using genetic algorithms

Abstract

Microarrays are emerging technologies that allow biologists to better understand the interactions between disease and normal states, at genes level. However, the amount of data generated by these tools becomes problematic when data are supposed to be automatically analyzed (e.g., for diagnostic purposes). In this work, the authors present a novel gene selection method based on Genetic Algorithms (GAs). The proposed method uses GAs to search for subsets of genes that optimize 2 measures of quality for the clusters presented in the domain. Thus, data are better represented and classification of unknown samples may become easier. In order to demonstrate the strength of the proposed approach, experimental results using 4 public available microarray datasets were carried out. © Springer-Verlag Berlin Heidelberg 2004.