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ParaKavosh: A Parallel Algorithm for Finding Biological Network Motifs

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Razaghi-Moghadam,  Z.
Mathematical Modelling and Systems Biology - Nikoloski, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Citation

Razaghi-Moghadam, Z., Masoudi-Nejad, A., & Nowzari-Dalini, A. (2020). ParaKavosh: A Parallel Algorithm for Finding Biological Network Motifs. In 2020 11th International Conference on Information and Knowledge Technology (IKT) (pp. 45-49).


Cite as: http://hdl.handle.net/21.11116/0000-0007-F5A3-C
Abstract
Biological networks have recently gathered much attraction in finding their motifs. Motifs can be considered as subgraphs that occur in a particular network at significantly higher frequencies than random networks. The importance of this problem causes attention of improving the existing algorithms. As the runtime of an algorithm is an important aspect, applying parallel techniques is appropriate for better improvement. In this paper a parallel algorithm (ParaKavosh) for finding network motifs is presented. Our algorithm is tested on E. coli, S. cerevisiae, Homo sapiens and Rattus norvegicus networks. The cost optimality of the algorithm is also shown by analyzing the obtained results with an efficient sequential algorithm. The results show that the algorithm performs much better in terms of runtime.