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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >An Ant Colony system for large-scale phylogenetic tree reconstruction
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An Ant Colony system for large-scale phylogenetic tree reconstruction

机译:用于大规模系统树重建的蚁群系统

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摘要

An important problem in Bioinformatics is the reconstruction of phylogenetic trees. A phylogenetic tree aims at unveiling the evolutionary relationship between several species. In this way, it is possible to know which species are more closely related to one another and which are more distantly related. Established methods for phylogeny work fine for small or moderate number of species, but they become unfeasible for large-scale phylogeny. This work proposes a methodology using the Ant Colony Optimization (ACO) paradigm for the problem. A phylogenetic tree is viewed as a fully-connected graph using a matrix of distances between species. We search for the shortest path in this graph, turning the problem to an instance of the well-known traveling salesman problem. After, we describe how to build a tree using the directed graph and the pheromone matrix obtained by the ACO. Two data sets were used to test the system. The first one was used to investigate the sensitivity of the control parameters and to define their default values. The second data set was used to analyze the scalability of the system for a large number of sequences. Results show that the proposed method is as good as or even better than the other conventional methods and very efficient for large-scale phylogeny.
机译:生物信息学中的一个重要问题是系统树的重建。系统发育树旨在揭示几种物种之间的进化关系。以这种方式,有可能知道哪些物种彼此之间的关系更紧密,哪些物种之间的关系更远。建立的系统发育方法对少量或中等数量的物种都适用,但对于大规模系统发育则不可行。这项工作提出了一种使用蚁群优化(ACO)范式解决该问题的方法。系统进化树被视为使用物种之间距离矩阵的完全连接图。我们在此图中搜索最短路径,将问题转为一个著名的旅行推销员问题的实例。之后,我们描述如何使用有向图和ACO获得的信息素矩阵来构建树。使用两个数据集来测试系统。第一个用于调查控制参数的敏感性并定义其默认值。第二个数据集用于分析大量序列的系统可伸缩性。结果表明,所提出的方法与其他常规方法一样好,甚至更好,并且对于大规模系统发育非常有效。

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