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Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules

机译:用于生物分子结构分析的多图比对的进化构建

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The concept of multiple graph alignment (MGA) has recently been introduced as a novel method for the structural analysis of biomolecules. Using approximate graph matching techniques, this method enables the robust identification of approximately conserved patterns in biologically related structures. In particular, MGA enables the characterization of functional protein families independent of sequence or fold homology. This article first recalls the concept of MGA and then addresses the problem of computing optimal alignments from an algorithmic point of view. In this regard, a method from the field of evolutionary algorithms is proposed and empirically compared with a hitherto existing heuristic approach. Empirically, it is shown that the former yields significantly better results than the latter, albeit at the cost of an increased runtime.Contact: eykeathematik.uni-marburg.deSupplementary information: Supplementary data are available at Bioinformatics online.
机译:最近引入了多重图对齐(MGA)的概念,作为一种生物分子结构分析的新方法。使用近似图匹配技术,该方法可以对生物学相关结构中的近似保守模式进行鲁棒性识别。特别地,MGA能够表征功能蛋白家族,而与序列或折叠同源性无关。本文首先回顾了MGA的概念,然后从算法的角度解决了计算最佳比对的问题。在这方面,提出了一种进化算法领域的方法,并将其与迄今已有的启发式方法进行了经验比较。从经验上可以看出,尽管增加了运行时间,但前者的结果要明显好于后者。联系人:eykeathematik.uni-marburg.de补充信息:补充数据可从在线生物信息学获得。

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