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  ParaKavosh: A Parallel Algorithm for Finding Biological Network Motifs

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).

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Razaghi-Moghadam, Z.1, Autor           
Masoudi-Nejad, A.2, Autor
Nowzari-Dalini, A.2, Autor
Affiliations:
1Mathematical Modelling and Systems Biology - Nikoloski, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753310              
2External Organizations, ou_persistent22              

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Schlagwörter: Knowledge engineering;Runtime;Biology;Parallel algorithms;Faces;Motifs;Bioinformatics;Parallel Algorithms
 Zusammenfassung: 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.

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Sprache(n): eng - English
 Datum: 2020-12
 Publikationsstatus: Erschienen
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 Identifikatoren: DOI: 10.1109/IKT51791.2020.9345641
BibTex Citekey: 9345641
 Art des Abschluß: -

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Titel: 2020 11th International Conference on Information and Knowledge Technology (IKT)
Genre der Quelle: Konferenzband
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 45 - 49 Identifikator: -