Pathway Analysis of Marker Genes for Leukemia Cancer using Enhanced Genetic Algorithm-Neural Network (enGANN)

Abstract

The model of gene-gene interaction contributing to the biological insight of disease pathology have received significant attention from both medical and computing communities. Through the modeled interactome map, the biological significant of the mutated genes can be revealed and treatments targeting these genes can be taken to prevent further proliferation of the mutated genes. In this paper we propose a novel computational way to interrogate interaction between genes. We utilize centroid computation in the hybrid genetic algorithm and neural network to model interaction between leukemia-related genes. Results indicated the effectiveness of centroid value in detecting significant interactions of gene. Hub genes were also identified.