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DNA Fragment Assembly Using Optimization: From nature inspired algorithms to formal methods

机译:使用优化的DNA片段组件:从自然启发算法到正式方法

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The DNA fragment assembly is an important phase required to obtain complete genomes. Optimization using nature inspired algorithms has been proposed by several authors. We present another nature inspired algorithm based on Particle Swarm Optimization and Differential Evolution. These algorithms are compared using a set of common benchmarks and showing some advantages in our proposed algorithm. We also applied the Traveling Salesman Problem (TSP) with better results than the nature inspired algorithms as we could obtain the true optima for 16 commonly used benchmarks for the first time to the best of our knowledge. The benchmarks are much smaller than the real organism assembly problems and scaling up from the benchmarks to real organisms presents important challenges. We propose a way to solve the scale up problems and test them using the Staphylococcus aureus COL Main Chromosome with the TSP approach.
机译:DNA片段组件是获得完整基因组所需的重要阶段。几个作者提出了使用自然启发算法的优化。我们介绍了基于粒子群优化和差分演进的另一种自然灵感算法。使用一组共同的基准进行比较这些算法,并以我们所提出的算法显示一些优点。我们还将旅行的推销员问题(TSP)应用于比性质灵感算法的更好的结果,因为我们可以在我们的知识中首次获得16个常用基准的真正Optima。基准比真正的有机体装配问题远小得多,并从基准到真正的生物的基准缩放都存在重要的挑战。我们提出了一种方法来解决规模问题,并使用TSP方法使用葡萄球菌的葡萄球菌的主要染色体来测试它们。

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