acc-Motif Detection Tool

Background: Network motif algorithms have been a topic of research mainly after the 2002-seminal paper from Milo et al, that provided motifs as a way to uncover the basic building blocks of most networks. In Bioinformatics, motifs have been mainly applied in the field of gene regulation networks field. Results: This paper proposes new algorithms to exactly count isomorphic pattern motifs of sizes 3, 4 and 5 in directed graphs. Let G(V, E) be a directed graph with m = |E|. We describe an O(m √ m) time complexity algorithm to count isomorphic patterns of size 3. In order to count isomorphic patterns of size 4, we propose an O(m) algorithm. To count patterns with 5 vertices, the algorithm is O(mn). Conclusion: The new algorithms were implemented and compared with FANMOD and Kavosh motif detection tools. The experiments show that our algorithms are expressively faster than FANMOD and Kavosh’s. We also let our motif-detecting tool available in the Internet. keywords: network motifs, complex networks, algorithm design and analysis, counting motifs, detecting motifs, motifs, discovery, motif isomorphism.