QuateXelero : an accelerated exact network motif detection algorithm
- Finding motifs in biological, social, technological, and other types of networks has become a widespread method to gain more knowledge about these networks’ structure and function. However, this task is very computationally demanding, because it is highly associated with the graph isomorphism which is an NP problem (not known to belong to P or NP-complete subsets yet). Accordingly, this research is endeavoring to decrease the need to call NAUTY isomorphism detection method, which is the most time-consuming step in many existing algorithms. The work provides an extremely fast motif detection algorithm called QuateXelero, which has a Quaternary Tree data structure in the heart. The proposed algorithm is based on the well-known ESU (FANMOD) motif detection algorithm. The results of experiments on some standard model networks approve the overal superiority of the proposed algorithm, namely QuateXelero, compared with two of the fastest existing algorithms, G-Tries and Kavosh. QuateXelero is especially fastest in constructing the central data structure of the algorithm from scratch based on the input network.
Author: | Sahand Khakabimamaghani, Iman Sharafuddin, Norbert Dichter, Ina KochORCiD, Ali Masoudi-Nejad |
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URN: | urn:nbn:de:hebis:30:3-311344 |
DOI: | https://doi.org/10.1371/journal.pone.0068073 |
ISSN: | 1932-6203 |
Parent Title (English): | PLoS One |
Publisher: | PLoS |
Place of publication: | Lawrence, Kan. |
Document Type: | Article |
Language: | English |
Date of Publication (online): | 2013/07/18 |
Date of first Publication: | 2013/07/18 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2013/08/19 |
Volume: | 8 |
Issue: | (7):e68073 |
Page Number: | 15 |
Note: | Copyright: © 2013 Khakabimamaghani et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
HeBIS-PPN: | 352050020 |
Institutes: | Biowissenschaften / Biowissenschaften |
Informatik und Mathematik / Informatik | |
Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke |
5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie | |
Sammlungen: | Universitätspublikationen |
Sammlung Biologie / Sondersammelgebiets-Volltexte | |
Licence (German): | Creative Commons - Namensnennung 3.0 |