Efficient Algorithm for Network Motifs Discovery

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Hazrati, Sattar | 2015

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 47535 (19)
University: Sharif University of Technology
Department: Computer Engineering
Advisor(s): Izadi, Mohammad
Abstract:
Network Motifs are subgraphs that appear more frequently in real networks than randomize networks. Frequent replication of a subgraph could imply evolution, network performance or some other particular reasons. From algorithmic perspective, network motif discovery in a graph is a difficult problem. Since, at least it includes the whole graph isomorphism. Hence, for solving this problem in practice, we need computable graphs. The existing algorithms so far, have high running times and memory usages. In this thesis, we present a new algorithm called CGQ. Within this algorithm, we use both QuateXelero and G-Trie algorithms which respectively have better performance in census of real networks and random networks. The proposed algorithm, outperforms both QuateXelero and G-Trie algorithms considering both running time and memory usage aspects and considering the memory usage it only falls behind Kavosh. We have given an implementation of the algorithm and have evaluated its performance against other algorithms under the same circumstances
Keywords:
Network ; Motif ; Algorithmic Efficiency ; Motif Discovery

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