机构地区:[1]State Key Laboratory for Manufacturing Systems Engineering and School of Electronic and Information Engineering,Xi’an Jiaotong University,Xi’an 710049,China [2]MOE Key Laboratory for Intelligent Networks and Network Security,Xi’an Jiaotong University,Xi’an 710049,China [3]Electronic and Information School of Xi’an Jiaotong University,Xi’an 710049,China
出 处:《Science China(Life Sciences)》2011年第2期139-145,共7页中国科学(生命科学英文版)
基 金:supported by the National Natural Science Foundation of China (Grant No. 60774086);the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20090201110027)
摘 要:Graves' disease,the production of thyroid-stimulating hormone receptor-stimulating antibodies leading to hyperthyroidism,is one of the most common forms of human autoimmune disease.It is widely agreed that complex diseases are not controlled simply by an individual gene or DNA variation but by their combination.Single nucleotide polymorphisms(SNPs),which are the most common form of DNA variation,have great potential as a medical diagnostic tool.In this paper,the P-value is used as a SNP pre-selection criterion,and a wrapper algorithm with binary particle swarm optimization is used to find the rule for discriminating between affected and control subjects.We analyzed the association between combinations of SNPs and Graves' disease by investigating 108 SNPs in 384 cases and 652 controls.We evaluated our method by differentiating between cases and controls in a five-fold cross validation test,and it achieved a 72.9% prediction accuracy with a combination of 17 SNPs.The experimental results showed that SNPs,even those with a high P-value,have a greater effect on Graves' disease when acting in a combination.Graves' disease,the production of thyroid-stimulating hormone receptor-stimulating antibodies leading to hyperthyroidism,is one of the most common forms of human autoimmune disease.It is widely agreed that complex diseases are not controlled simply by an individual gene or DNA variation but by their combination.Single nucleotide polymorphisms(SNPs),which are the most common form of DNA variation,have great potential as a medical diagnostic tool.In this paper,the P-value is used as a SNP pre-selection criterion,and a wrapper algorithm with binary particle swarm optimization is used to find the rule for discriminating between affected and control subjects.We analyzed the association between combinations of SNPs and Graves' disease by investigating 108 SNPs in 384 cases and 652 controls.We evaluated our method by differentiating between cases and controls in a five-fold cross validation test,and it achieved a 72.9% prediction accuracy with a combination of 17 SNPs.The experimental results showed that SNPs,even those with a high P-value,have a greater effect on Graves' disease when acting in a combination.
关 键 词:Graves' disease single nucleotide polymorphism case-control study swarm intelligence
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