【摘要】 针对全基因组规模的上位性分析中存在的问题,首先采用基于多准则融合的过滤法对大量变异位点进行筛选以过滤无关位点,并结合蚁群算法对变异位点进行上位性分析,从而进一步剔除冗余位点,最后采用支持向量机作为上位性与复杂疾病关系的分类模型.实验结果表明,先过滤再分类的策略,不仅大大降低了上位性时间复杂度,并且在分类准确度上也有一定程度提高.更多还原

【Abstract】 To solve the problem of epistasis analysis in genome-wide,a filter method based on multiple criteria fusion was developed to remove the unrelated SNP loci.After that,ant colony algorithm was used to construct the SNP set with epistasis interaction.In the phase of constructing,a support vector machine was proposed to build the relationship between the SNP set and complex diseases.The experiment results show that,with multiple criteria evaluating each SNP and ant colony optimization,the prediction accuracy and running time have been improved,making it better than conventional methods.更多还原