Gene reduction for cancer classification using cascaded neural network with gene masking

Abstract

This paper presents an approach to cancer classification from gene expression profiling using cascaded neural network classifier. The method used aims to reduce the genes required to successfully classify the small round blue cell tumours of childhood (SRBCT) into four categories. The system designed to do this consists of a feedforward neural network and is trained with genetic algorithm. A concept of 'gene masking' is introduced to the system which significantly reduces the number of genes required for producing very high accuracy classification. © 2014 Springer International Publishing.