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Optimal solutions for the balanced minimum evolution problem

机译:平衡的最小演化问题的最优解

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Phytogenies are trees representing the evolutionary relationships of a set of species (called taxa). Phylogenies find application in several scientific areas ranging from medical research to drug discovery, epidemiology, systematics and population dynamics. In these applications the available information is usually restricted to the leaves of a phylogeny and is represented by molecular data extracted from the species analyzed. On the contrary, the information about the phylogeny itself is generally missing and must be determined by solving an optimization problem, called the phylogeny estimation problem (PEP), whose versions depend on the criterion used to select a phylogeny among plausible alternatives. In this paper, we investigate one of the most significant versions of the PEP, called the balanced minimum evolution problem. We propose an exact algorithm based on the enumeration of non-isomorphic trees and the subsequent solution of quadratic assignment problems. Furthermore, by exploiting the underlying parallelism of the algorithm, we present a parallel version of the algorithm which shows a linear speed-up with respect to the sequential version. Extensive computational results prove the effectiveness of the proposed algorithms.
机译:植物学是代表一组物种(称为分类群)进化关系的树木。系统发育在医学研究到药物发现,流行病学,系统学和种群动态等多个科学领域中都有应用。在这些应用中,可用信息通常仅限于系统发育的叶子,并由从所分析物种中提取的分子数据表示。相反,有关系统发育本身的信息通常会丢失,必须通过解决称为系统发育估计问题(PEP)的优化问题来确定,该问题的版本取决于在可能的替代方案中选择系统发育的标准。在本文中,我们研究了PEP的最重要版本之一,称为平衡最小演化问题。我们提出了一种基于非同构树的枚举和二次分配问题的后续解决方案的精确算法。此外,通过利用算法的基础并行性,我们提出了该算法的并行版本,该并行版本显示了相对于顺序版本的线性加速。大量的计算结果证明了所提算法的有效性。

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