Gene discovery in leukemia revisited: A computational intelligence perspective

Abstract

An approach using clustering in combination with Rough Sets and neural networks was investigated for the purpose of gene discovery using leukemia data. A small number of genes with high discrimination power were found, some of which were not previously reported. It was found that subtle differences between very similar genes belonging to the same cluster, as well as the number of clusters constructed, affect the discovery of relevant genes. Good results were obtained with no preprocessing applied to the data.