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Discovering genomic islands in microbial genomes using a genetic algorithm

机译:使用遗传算法发现微生物基因组中的基因组岛

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Genetic materials are exchanged very frequently across microbial organisms. In many cases, a cluster of adjacent genes, rather than individual genes, are transferred from one genome into another genome. The influx gene clusters in the recipient genome are also known as genomic islands (GIs). While various computational approaches have been employed to identify genomic islands, they are not universally applicable to predict any microbial genome. In this paper, we propose a genetic algorithm (GA) approach to search genomic islands for any genome. The GA evaluates candidate solutions in the population based on sequence composition based fitness value, and finds final solutions through crossover and mutation operations throughout the evolution. We applied our GA approach on four genomes. Experimental results have shown that our GA could not only find previously reported GIs, but also find some new GIs not reported before. We believe that our GA-based approach for GI finding should complement existing GI prediction tools.
机译:遗传物质在微生物之间非常频繁地交换。在许多情况下,相邻基因的簇而不是单个基因从一个基因组转移到另一个基因组。受体基因组中的潮涌基因簇也称为基因岛。尽管已经采用了各种计算方法来识别基因组岛,但是它们并不能普遍适用于预测任何微生物基因组。在本文中,我们提出了一种遗传算法(GA)方法来搜索基因组岛以寻找任何基因组。 GA根据基于序列组成的适应性值评估总体中的候选解决方案,并在整个进化过程中通过交叉和突变操作找到最终解决方案。我们将GA方法应用于四个基因组。实验结果表明,我们的遗传算法不仅可以找到以前报告的地理标志,而且还可以找到以前未报告的一些新的地理标志。我们认为,我们基于遗传算法的地理标志查找方法应能补充现有的地理标志预测工具。

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