Hybridising Genetic Algorithm-Neural Network (GANN) in marker genes detection

The identification of marker genes trigger the growth of mutated cells has received a significant attention from both medical and computing communities. Through the identified genes, the pathology of mutated cells can be revealed and precautions can be taken to prevent further proliferation of abnormal cells. In this paper, we propose an innovative gene identification framework based on genetic algorithms and neural networks to identify marker genes for leukaemia cancer. Our approach able to provide a sharper focus on a group of highly expressed genes in leukaemia dataset and the identified genes have been proven significant to the study of leukaemia cancer development.