STRUCTURAL MOTIF ENUMERATION IN TRANSCRIPTIONAL REGULATION NETWORKS

Claire Luciano, Chun-Hsi Huang

Abstract

Network motifs are small connected subnetworks within a larger network that occur in statistically significant quantities and may indicate functional regions of the network. Network motif software tools employ algorithms that compare a network to randomly generated networks in order to identify subnetworks that occur in frequencies higher than would be expected by random chance. The transcriptional regulation network of E. coli has been represented as a network and evaluated using both full enumeration and an edge sampling algorithm. Several significant network motifs were identified, including feedforward loops and bipartite graphs. This paper applies both full enumeration and a different sampling algorithm, randomized enumeration, to the E. coli network using the newer software tool FANMOD. Evaluating the E. coli transcriptional regulation network with FANMOD also identified feedforward loops and bipartite graphs as significant network motifs. Sampling identified fewer and less significant motifs than full enumeration, however, sampling enables the evaluation of larger subgraph sizes.

References

  1. Kashtan, N., Itzkovitz, K., Milo, R. and Alon, U. (2004) “Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs”, Bioinformatics, 20(11):1746-1758.
  2. Lee, Tong Ihn et al. (2002) “Transcriptional Regulatory Networks in Saccharomyces Cerevisiae,” Science, 298(5594):799-804.
  3. McKay, B. (1981) “Practical Graph Isomorphism”, Congressus Numerantium, Vol 30, 45-87.
  4. Milo, R., Shen-Orr, S. Itzkovitz, K., Chklovskii, D. and Alon, U. (2002) “Network Motifs: Simple Building Blocks of Complex Networks”, Science, 298(5594):824-827.
  5. Schreiber. F. and Schwobbermeyer, H. (2005) “Mavisto: a tool for the exploration of network motifs,” Bioinformatics, 21(17), 3572-3574.
  6. Shen-Orr, Shai S., Milo, R., Mangan, S. and Alon, U. (2002) “Network motifs in the transcriptional regulation network of Escherichia coli,” Nature Genetics, Vol 31, 64-68.
  7. Wernicke, S. and Rasche, F. (2006) “FANMOD: a tool for fast network motif detection,” Bioinformatics, 22(9):1152-1153.
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Paper Citation


in Harvard Style

Luciano C. and Huang C. (2010). STRUCTURAL MOTIF ENUMERATION IN TRANSCRIPTIONAL REGULATION NETWORKS . In Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010) ISBN 978-989-674-019-1, pages 187-192. DOI: 10.5220/0002760001870192


in Bibtex Style

@conference{bioinformatics10,
author={Claire Luciano and Chun-Hsi Huang},
title={STRUCTURAL MOTIF ENUMERATION IN TRANSCRIPTIONAL REGULATION NETWORKS},
booktitle={Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010)},
year={2010},
pages={187-192},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002760001870192},
isbn={978-989-674-019-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010)
TI - STRUCTURAL MOTIF ENUMERATION IN TRANSCRIPTIONAL REGULATION NETWORKS
SN - 978-989-674-019-1
AU - Luciano C.
AU - Huang C.
PY - 2010
SP - 187
EP - 192
DO - 10.5220/0002760001870192