Generalized neurons and its application in DNA microarray classification

Abstract

The DNA Microarray classification is an important task in bioinformatics and medicine area. The genetic expression in DNA microarrays present the opportunity to determine for example, which genes are involved with a particular disease, identify tumors, select the best treatment, etc. Several computational intelligence technique such as artificial neural networks can be used to identify different groups of genes associated with a particular disease. However, the enormous quantity of genes and the few samples available demand the use of more robust artificial neural networks. The purpose of this research is focused on showing how a generalize neuron (GN) can be applied in the DNA microarray classification task. In order to do that, the proposed methodology first, select the set of genes that best describe the disease applying the artificial bee colony algorithm. After that, the genes found during the first stage are used to train a GN. The GN is trained with the differential evolution algorithm. Finally, the accuracy of the proposed methodology is tested classifying two type of cancer using DNA microarrays: the acute lymphocytic leukemia and the acute myeloid leukemia.