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A novel ant based algorithm for multiple graph alignment

机译:一种新颖的基于蚂蚁的多图对齐算法

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Multiple graph alignment (MGA) is a new approach to analyze protein structure in order to exploring their functional similarity. In this article, we propose a two-stage memetic algorithm to solve the MGA problem, named ACO-MGA2, based on ant colony optimization metaheuristic. A local search procedure is applied only to the second stage of the algorithm to save runtime. Experimental results have shown that ACO-MGA2 outperforms state-of-the-art algorithms while producing alignments of better quality.
机译:多曲线图对齐(MGA)是分析蛋白质结构的新方法,以探索其功能性相似性。在本文中,我们提出了一种基于蚁群优化成式的蚁群优化成群化来解决ACO-MGA2的MGA问题的两级迭代算法。将本地搜索过程仅应用于算法的第二阶段以保存运行时。实验结果表明,ACO-MGA2优于最先进的算法,同时产生更好质量的对准。

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