Publication | Closed Access
Heuristics for Similarity Searching of Chemical Graphs Using a Maximum Common Edge Subgraph Algorithm
150
Citations
15
References
2002
Year
Chemical GraphsEngineeringNetwork AnalysisChemistryGraph MatchingChemical Graph SimilarityGraph ProcessingGraph SimilarityData ScienceData MiningStructural Graph TheoryRascal Similarity CalculationCombinatorial OptimizationSimilarity SearchingKnowledge DiscoveryComputer ScienceGraph AlgorithmNetwork ScienceGraph TheoryComputational BiologyNetwork BiologyBusinessGraph Analysis
Recently a method (RASCAL) for determining graph similarity using a maximum common edge subgraph algorithm has been proposed which has proven to be very efficient when used to calculate the relative similarity of chemical structures represented as graphs. This paper describes heuristics which simplify a RASCAL similarity calculation by taking advantage of certain properties specific to chemical graph representations of molecular structure. These heuristics are shown experimentally to increase the efficiency of the algorithm, especially at more distant values of chemical graph similarity.
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