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Finding DNA Motifs with Collective Parallel Artificial Bee Colony Algorithm

机译:使用集体并行人工蜂群算法查找DNA图案

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Metaheuristic techniques have been successfully used to produce feasible solutions within the acceptable execution times for complex numerical or combinatorial problems on behalf of classical optimization or search techniques in recent years. The successes of the existing metaheuristic techniques also lead to increase the number of applications focused on solving bioinformatics problems. In this study, a new parallel implementation of the Artificial Bee Colony (ABC) algorithm named cooperative parallel ABC algorithm was used for finding common nucleotide sequences or motifs within DNA strings. Experimental results obtained with the studies on extracting motifs from the DNA sequences of human showed that cooperative model based parallel ABC algorithm is capable of finding more qualified solutions compared to conventional serial and parallel model of the same algorithm.
机译:近年来,元启发式技术已成功用于代表复杂的数值或组合问题,在可接受的执行时间内针对复杂的数值或组合问题产生可行的解决方案。现有元启发式技术的成功也导致专注于解决生物信息学问题的应用程序数量增加。在这项研究中,人工蜂群(ABC)算法的一种新的并行实现称为协作并行ABC算法,用于发现DNA字符串中的常见核苷酸序列或基序。通过从人类DNA序列中提取基序的研究获得的实验结果表明,与基于相同模型的常规串行和并行模型相比,基于协作模型的并行ABC算法能够找到更多合格的解决方案。

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