Network motifs, feedback loops and the dynamics of genetic regulatory networks

J. S. Hallinan*, P. T. Jackway

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

14 Citations (Scopus)

Abstract

We analyse a suite of Boolean networks which have been evolved to exhibit limit cycle-type dynamics in terms of the distribution of small network motifs and feedback loops. We find that asynchronously updated Boolean networks can be evolved to exhibit fuzzy limit cycle dynamics without significant changes to the number of nodes and links in the network. Analysis of all possible triads of nodes in the networks and all feedback loops of length one to eight reveal no significant differences between the evolved and unevolved networks. We conclude that the reductionist, motif-based approach to network analysis may be inadequate to full understanding of network dynamics, and that some dynamic behaviour is an emergent property of complex networks as a whole.

Original languageEnglish
Title of host publication2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-7
Number of pages7
ISBN (Print)0780393872, 9780780393875
Publication statusPublished - 2005
Externally publishedYes
Event2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05 - La Jolla, CA, United States
Duration: 14 Nov 200515 Nov 2005

Other

Other2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB '05
CountryUnited States
CityLa Jolla, CA
Period14/11/0515/11/05

Fingerprint Dive into the research topics of 'Network motifs, feedback loops and the dynamics of genetic regulatory networks'. Together they form a unique fingerprint.

  • Cite this

    Hallinan, J. S., & Jackway, P. T. (2005). Network motifs, feedback loops and the dynamics of genetic regulatory networks. In 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (pp. 1-7). [1594903] Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE).