Enhancing Graph Database Indexing by Suffix Tree Structure

  • Vincenzo Bonnici
  • Alfredo Ferro
  • Rosalba Giugno
  • Alfredo Pulvirenti
  • Dennis Shasha
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6282)


Biomedical and chemical databases are large and rapidly growing in size. Graphs naturally model such kinds of data. To fully exploit the wealth of information in these graph databases, scientists require systems that search for all occurrences of a query graph. To deal efficiently with graph searching, advanced methods for indexing, representation and matching of graphs have been proposed.

This paper presents GraphGrepSX. The system implements efficient graph searching algorithms together with an advanced filtering technique.

GraphGrepSX is compared with SING, GraphFind, CTree and GCoding. Experiments show that GraphGrepSX outperforms the compared systems on a very large collection of molecular data. In particular, it reduces the size and the time for the construction of large database index and outperforms the most popular systems.


subgraph isomorphism graph database search indexing suffix tree molecular database 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Vincenzo Bonnici
    • 1
  • Alfredo Ferro
    • 1
  • Rosalba Giugno
    • 1
  • Alfredo Pulvirenti
    • 1
  • Dennis Shasha
    • 2
  1. 1.Dipartimento di Matematica ed InformaticaUniversità di CataniaCataniaItaly
  2. 2.Courant Institute of Mathematical SciencesNew York UniversityNew YorkUSA

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