QuateXelero: An Accelerated Exact Network Motif Detection Algorithm

PLoS ONE

Volumn 8, Issue 7, 2013, Pages

  Khakabimamaghani, Sahand ^a   Sharafuddin, Iman ^a   Dichter, Norbert ^b   Koch, Ina ^b   Masoudi Nejad, Ali ^a  

^a UNIVERSITY OF TEHRAN   (Iran)

^b GOETHE UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; CLASSIFICATION; COMPUTER ANALYSIS; COMPUTER LANGUAGE; COMPUTER NETWORK; COMPUTER PROGRAM; DOLPHIN; ESCHERICHIA COLI; METHODOLOGY; NONHUMAN; PROTEIN QUATERNARY STRUCTURE; YEAST;

ALGORITHMS; CLASSIFICATION; COMPUTER SIMULATION; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED; TIME FACTORS;

EID: 84880408672     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0068073     Document Type: Article

References (21)

1. Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, et al. (2002) Network motifs: simple building blocks of complex networks. Science 298: 824-827.
2. Dekel E, Mangan S, Alon U, (2005) Environmental selection of the feed-forward loop circuit in gene-regulation networks. Physical biology 2: 81-88.
3. Zabet NR, (2011) Negative feedback and physical limits of genes. Journal of theoretical biology 284: 82-91.
4. Mangan S, Alon U, (2003) Structure and function of the feed-forward loop network motif. Proceedings of the National Academy of Sciences of the United States of America 100: 11980-11985.
5. Wernicke S, Rasche F, (2006) FANMOD: a tool for fast network motif detection. Bioinformatics 22: 1152-1153.
6. Kashani ZR, Ahrabian H, Elahi E, Nowzari-Dalini A, Ansari ES, et al. (2009) Kavosh: a new algorithm for finding network motifs. BMC bioinformatics 10: 318.
7. Grochow JA, Kellis M (2007) Network Motif Discovery Using Sub-graph Enumeration and Symmetry-Breaking. RECOMB. 92-106.
8. Ribeiro P, Silva F (2010) G-Tries: an efficient data structure for discovering network motifs. 25th ACM Symposium on Applied Computing- Bioinformatics and Computational Systems Biology Track, Sierre, Switzerland.
9. Wang J, Huang Y, Wu FX, Pan Y (2012) Symmetry Compression method for Discovering Network Motifs. IEEE/ACM transactions on computational biology and bioinformatics/IEEE, ACM 10A02234-FB2C-42D1-AE5A-CA813BF34133.
10. Beber ME, Fretter C, Jain S, Sonnenschein N, Muller-Hannemann M, et al. (2012) Artefacts in statistical analyses of network motifs: general framework and application to metabolic networks. Journal of the Royal Society, Interface/the Royal Society 9: 3426-3435.
11. Omidi S, Schreiber F, Masoudi-Nejad A, (2009) MODA: an efficient algorithm for network motif discovery in biological networks. Genes & genetic systems 84: 385-395.
12. Brendan M, (1981) Practical Graph Isomorphism. Congressus Numerantium 30: 45-87.
13. Ribeiro P, Silva F, Kaiser M (2009) Strategies for Network Motifs Discovery. Fifth IEEE International Conference on e-Science. 80-87.
14. Darga P, Sakallah K, Markov IL (2008) Faster Symmetry Discovery using Sparsity of Symmetries. The 45st Design Automation Conference. 149-154.
15. Junttila T, Kaski P (2007) Engineering an efficient canonical labeling tool for large and sparse graphs. the Ninth Workshop on Algorithm Engineering and Experiments (ALENEX07).
16. The E.coli Database. Available: http://www.kegg.com/.
17. The S. cerevisiae Database. Available: http://www.weizmann.ac.il/mcb/UriAlon/.
18. Bu D, Zhao Y, Cai L, Xue H, Zhu X, et al. (2003) Topological structure analysis of the protein-protein interaction network in budding yeast. Nucleic acids research 31: 2443-2450.
19. Batagelj M, Mrvar A (2006) Pajek Datasets. Available: http://vlado.fmf.uni-lj.si/pub/networks/data/.
20. Lusseau D, Schneider K, Boisseau OJ, Haase P, Slooten E, et al. (2003) The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations. can geographic isolation explain this unique trait? Behavioral Ecology and Sociobiology 54: 396-405.
21. Newman M (2009) Network Data. Available: http://www-personal.umich.edu/~mejn/netdata/.