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Comparison of Maximum Common Subgraph Isomorphism Algorithms for the Alignment of 2D Chemical Structures

机译:2D化学结构对准最大常见子图同构算法的比较

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The identification of the largest substructure in common when two (or more) molecules are overlaid is important for several applications in chemoinformatics, and can be implemented using a maximum common subgraph (MCS) algorithm. Many such algorithms have been reported, and it is important to know which are likely to be the useful in operation. A detailed comparison was hence conducted of the efficiency (in terms of CPU time) and the effectiveness (in terms of the size of the MCS identified) of eleven MCS algorithms, some of which were exact and some of which were approximate in character. The algorithms were used to identify both connected and disconnected MCSs on a range of pairs of molecules. The fastest exact algorithms for the connected and disconnected problems were found to be the fMCS and MaxCliqueSeq algorithms, respectively, while the ChemAxon_MCS algorithm was the fastest approximate algorithm for both types of problem.
机译:当两个(或更多)分子重叠时,鉴定最大的子结构,对于在化疗中的若干应用中是重要的,并且可以使用最大常见的子图(MCS)算法来实现。 已经报道了许多这样的算法,并且知道哪个可能是在操作中有用的。 因此,详细的比较是对11个MCS算法的效率(根据CPU时间)和有效性(根据鉴定的MCS的大小),其中一些是精确的,其中一些是近似的特征。 该算法用于识别一系列分子上的连接和断开的MCS。 发现连接和断开问题的最快精确算法分别是FMC和MaxCliqueSQ算法,而ChemaxOn_MCS算法是两种类型的最快近似算法。

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