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首页> 外文期刊>Journal of Experimental & Theoretical Artificial IntelligencernArtificial Intelligence >Honey bee-inspired algorithms for SNP haplotype reconstruction problem
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Honey bee-inspired algorithms for SNP haplotype reconstruction problem

机译:蜜蜂启发算法解决SNP单倍型重建问题

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摘要

Reconstructing haplotypes from SNP fragments is an important problem in computational biology. There have been a lot of interests in this field because haplotypes have been shown to contain promising data for disease association research. It is proved that haplotype reconstruction in Minimum Error Correction model is an NP-hard problem. Therefore, several methods such as clustering techniques, evolutionary algorithms, neural networks and swarm intelligence approaches have been proposed in order to solve this problem in appropriate time. In this paper, we have focused on various evolutionary clustering techniques and try to find an efficient technique for solving haplotype reconstruction problem. It can be referred from our experiments that the clustering methods relying on the behaviour of honey bee colony in nature, specifically bees algorithm and artificial bee colony methods, are expected to result in more efficient solutions. An application program of the methods is available at the following link.
机译:从SNP片段重建单倍型是计算生物学中的重要问题。由于单倍型已被证明包含有希望用于疾病关联研究的数据,因此在该领域引起了很多兴趣。证明最小纠错模型中的单倍型重建是一个NP难题。因此,已经提出了几种方法,例如聚类技术,进化算法,神经网络和群体智能方法,以在适当的时间解决该问题。在本文中,我们集中于各种进化聚类技术,并试图找到一种解决单倍型重构问题的有效技术。从我们的实验中可以看出,依赖自然界中蜂群行为的聚类方法,特别是蜂算法和人工蜂群方法,有望产生更有效的解决方案。以下链接提供了这些方法的应用程序。

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