Ant Colony Optimization Vs Genetic Algorithm to Calculate Gene Order of Gene Expression Level of Alzheimer's Disease
IEEE International Conference on Granular Computing(2012)
摘要
Alzheimer's disease (AD) is the most common form of dementia, the study of AD gene plays key role. Analyzing gene expression levels obtained from cDNA microarray becomes popular currently. Gene order is defined as the order of genes: If two genes holding closed expression levels on multi-variables, they are neighbors to each other and are put together linearly. The optimal gene order means that all neighbors of genes are ordered together linearly and the order is optimum. And optimal gene order is helpful to study AD. In this paper, gene order is characterized as the route of TSP (traveling salesman problem) on multidimensional space. Then two typical computation tools of TSP Genetic Algorithm (GA) and Ant Colony Optimization (ACO) are used to calculated gene order. The following conclusions are suggested by the experiment of this paper: ACO fits AD gene best to calculate gene order; Different distance formulas generate different quality of gene order for both GA and ACo. Therefore, ACO might be the first choice to calculate gene order.
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关键词
Ant Colony Optimization,Genetic Algorithm,Gene Order,Gene Expression Level,Alzheimer's Disease
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