Finding frequent subgraphs in biological networks via maximal item sets

H. Zantema, S. Wagemans, D. Bosnacki

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

2 Citaten (Scopus)
3 Downloads (Pure)


We describe an improvement of an algorithm for detecting frequently occurring patterns and modules in biological networks. The improvement is based on the observation that the problem of finding frequent network parts can be reduced to the problem of finding maximal frequent item sets (MFI). The MFI problem is a classical problem in the data mining community and there exist numerous efficient tools for it, most of them publicly available. We apply MFI tools to find frequent subgraphs in metabolic pathways from the KEGG database. Our experimental results show that, compared to the existing specialized tools for frequent subgraphs detection, the MFI tools coupled with an adequate postprocessing are much more efficient with regard to the running time and the size of the frequent graphs.
Originele taal-2Engels
TitelBioinformatics Research and Development (2nd International Conference, BIRD'08, Vienna, Austria, July 7-9, 2008, Proceedings)
RedacteurenM. Elloumi, J. Küng, M. Linial, R. Murphy, K. Schneider, C. Toma
Plaats van productieBerlin
ISBN van geprinte versie978-3-540-70598-7
StatusGepubliceerd - 2008

Publicatie series

NaamCommunications in Computer and Information Science
ISSN van geprinte versie1865-0929


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