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Classification of Cattle Coat Color Based on Genotype Using Pattern Recognition Methods

机译:基于基因型使用模式识别方法对牛涂层的分类

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Several current research projects are focused on the creation of haplotype maps to identify and describe common genetic variation in some species. Studies on haplotype maps are key in understanding how natural selection has produced genomic differences between subspecies of a given species. Important insight can be obtained by determining which variations in the genotype are associated with important phenotypical differences between individuals. Pattern recognition theory and machine learning techniques are useful tools to reveal this connection from a large amount of data provided by haplotype maps. In this work, we applied discrete classifiers and feature selection techniques for the prediction of cattle coat color from genotypes. We compared the performance of different classification rules and showed the feasibility of this approach for the prediction of phenotype based on genotype.
机译:几个目前的研究项目集中在创建单倍型地图以识别和描述某些物种中的常见遗传变异。对单倍型图的研究是了解自然选择在给定物种的亚种之间产生基因组差异的关键。可以通过确定基因型的哪种变化与个体之间的重要表型差异相关的重要见解。模式识别理论和机器学习技术是有用的工具,可以从单倍型映射提供的大量数据中揭示此连接。在这项工作中,我们应用了离散的分类器和特征选择技术,从基因型中预测牛涂色。我们比较了不同分类规则的性能,并表明了这种方法对基于基因型预测表型的方法的可行性。

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