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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Local Clique Merging: An Extension of the Maximum Common Subgraph Measure with Applications in Structural Bioinformatics
verfasst von : Thomas Fober, Gerhard Klebe, Eyke Hüllermeier
Erschienen in: Algorithms from and for Nature and Life
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Abstract
We develop a novel similarity measure for node-labeled and edge-weighted graphs, which is an extension of the well-known maximum common subgraph (MCS) measure. Despite its common usage and appealing properties, the MCS also exhibits some disadvantages, notably a lack of flexibility and tolerance toward structural variation. In order to address these issues, we propose a generalization which is based on so-called quasi-cliques. A quasi-clique is a relaxation of a clique in the sense of being an “almost” complete subgraph. Thus, it increases flexibility and robustness toward structural variation. To construct a quasi-clique, we make use of a heuristic approach, in which so-called local cliques are determined first and combined into larger (quasi-)cliques afterward. We also present applications of our novel similarity measure to the retrieval and classification of protein binding sites.