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A Parallel Multiobjective Algorithm Inspired by Fireflies for Inferring Evolutionary Trees on Multicore Machines

机译:由Fireflies启发的并行多目标算法,用于在多核机器上推断进化树

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Recent researches have pointed out the need to combine parallelism and bioinspired computing to address computationally intensive problems in bioinformatics. The inference of evolutionary histories represents one of the most complex problems in this field. Phylogenetic inference can be tackled by using multiobjective metaheuristics designed to resolve the problems that arise when different optimality criteria support conflicting evolutionary relationships. As the inference process becomes harder when we have to consider multiple criteria simultaneously, these new approaches must be defined on the basis of parallel computing. In this paper, we propose a parallel multiobjective approach inspired by fireflies to address the phylogenetic inference problem by using OpenMP to exploit the characteristics of multicore machines. Experimental results on four real biological data sets show significant parallel and biological performances with regard to other proposals from the literature.
机译:最近的研究表明需要将平行和生物透露计算结合起来以解决生物信息学中的计算密集问题。进化历史的推断是该领域中最复杂的问题之一。通过使用旨在解决不同的最优性标准支持冲突的进化关系时出现的问题来解决系统发育推理。由于推理过程在我们必须同时考虑多个标准时更难,因此必须基于并行计算来定义这些新方法。在本文中,我们提出了一种平行的多目标方法,其灵感来自萤火虫通过使用OpenMP利用多核机器的特性来解决系统发育推理问题。四种真实生物数据集的实验结果表明,关于文献的其他提案,显着平行和生物学性能。

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