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A New Parallel Asynchronous Cellular Genetic Algorithm for de Novo Genomic Sequencing

机译:用于DE Novo基因组测序的新并联异步细胞遗传算法

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This work proposes a new parallel asynchronous cellular genetic algorithm model for multi-core processors. The algorithm has been used for solving the DNA fragment assembly problem with the aim of finding highly accurate solutions in short computation times. This NP-Complete problem lies in reconstructing a DNA chain from multiple fragments that have previously been sequenced in a laboratory. The considered problem is a critical step in any genomic project, since the resulting chains are the basis for the entire work. Therefore, the quality of these chains is a major aspect for the correct development of the project. The proposed algorithm is able to find highly accurate results much faster than the other algorithms in the literature. Additionally, since it is parallel, it could be scalable to much larger problem instances, for which the methods typically used usually encounter difficulties. Finally, several new local search methods have been designed, and their influence on the performance of the algorithm has been analyzed.
机译:这项工作提出了一种用于多核处理器的新的并联异步蜂窝遗传算法模型。该算法已被用于解决DNA片段组装问题,目的是在短的计算时间内找到高精度的解决方案。该NP完全的问题在于从先前在实验室中测序的多个片段重建DNA链。被认为的问题是任何基因组项目的关键步骤,因为所得到的链是整个工作的基础。因此,这些链条的质量是项目正确发展的主要方面。所提出的算法能够比文献中的其他算法快得多的高精度结果。另外,由于它是平行的,它可以可扩展到更大的问题实例,其中通常使用的方法通常遇到困难。最后,已经设计了几种新的本地搜索方法,并分析了它们对算法性能的影响。

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