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Kavosh: a new algorithm for finding network motifs
Institute of Biochemistry and Biophysics, University of Tehran. (Laboratory of Systems Biology and Bioinformatics)
School of Mathematics and Computer Science, University of Tehran.
School of Biology, University of Tehran.
School of Mathematics and Computer Science, University of Tehran.
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2009 (English)In: BMC Bioinformatics, ISSN 1471-2105, Vol. 10, no 318Article in journal (Refereed) Published
Abstract [en]


Complex networks are studied across many fields of science and are particularly important to understand biological processes. Motifs in networks are small connected sub-graphs that occur significantly in higher frequencies than in random networks. They have recently gathered much attention as a useful concept to uncover structural design principles of complex networks. Existing algorithms for finding network motifs are extremely costly in CPU time and memory consumption and have practically restrictions on the size of motifs.


We present a new algorithm (Kavosh), for finding k-size network motifs with less memory and CPU time in comparison to other existing algorithms. Our algorithm is based on counting all k-size sub-graphs of a given graph (directed or undirected). We evaluated our algorithm on biological networks of E. coli and S. cereviciae, and also on non-biological networks: a social and an electronic network.


The efficiency of our algorithm is demonstrated by comparing the obtained results with three well-known motif finding tools. For comparison, the CPU time, memory usage and the similarities of obtained motifs are considered. Besides, Kavosh can be employed for finding motifs of size greater than eight, while most of the other algorithms have restriction on motifs with size greater than eight. The Kavosh source code and help files are freely available at:

Place, publisher, year, edition, pages
BioMed Central: BioMed Central Ltd. , 2009. Vol. 10, no 318
National Category
Computer Science
Research subject
Computer Science
URN: urn:nbn:se:oru:diva-24127DOI: 10.1186/1471-2105-10-318OAI: diva2:541191
Available from: 2012-08-07 Created: 2012-07-15 Last updated: 2012-08-07Bibliographically approved

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Asadi, Sahar
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School of Science and Technology, Örebro University, Sweden
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