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Data Mining in Complex Diseases Using Evolutionary Computation

机译:使用进化计算的复杂疾病数据挖掘

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摘要

A new algorithm is presented for finding genotype-phenotype association rules from data related to complex diseases. The algorithm was based on Genetic Algorithms, a technique of Evolutionary Computation. The algorithm was compared to several traditional data mining techniques and it was proved that it obtained similar classification scores but found more rules from the data generated artificially. In this paper it is assumed that several groups of SNPs have an impact on the predisposition to develop a complex disease like schizophrenia. It is expected to validate this in a short period of time on real data.
机译:提出了一种新算法,用于从与复杂疾病有关的数据中寻找基因型与表型的关联规则。该算法基于遗传算法,一种进化计算技术。将该算法与几种传统的数据挖掘技术进行了比较,证明该算法获得了相似的分类评分,但从人工生成的数据中发现了更多的规则。在本文中,假定几组SNP对易患精神分裂症等复杂疾病的易感性产生影响。期望在短时间内对真实数据进行验证。

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