Reconstruction and update robustness of the mammalian cell cycle network

Gonzalo A. Ruz, Eric Goles

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Given the input-output data of the mammalian cell cycle network under a parallel updating scheme, an attempt to construct a threshold Boolean network with the same dynamics is presented. To accomplish this, mutual information is used to find the network structure, then a swarm intelligence optimization technique called the bees algorithm is used to find the weights and thresholds for the network. It is shown that out of the ten regulatory elements (nodes) of the network, only nine can be modeled as a single threshold function, thus, the resulting network is almost a threshold Boolean network with the exception of the CycA protein which remains with its logical rules instead. The robustness of the network is explored with respect to update perturbations, in particular, what happens to the limit cycle attractors when changing from parallel to a sequential updating scheme. Results shows that the network is not robust since different limit cycles of different lengths appear.

Original languageEnglish
Title of host publication2012 IEEE Symposium on Computational Intelligence and Computational Biology, CIBCB 2012
Pages397-403
Number of pages7
DOIs
StatePublished - 2012
Event2012 IEEE Symposium on Computational Intelligence and Computational Biology, CIBCB 2012 - San Diego, CA, United States
Duration: 9 May 201212 May 2012

Publication series

Name2012 IEEE Symposium on Computational Intelligence and Computational Biology, CIBCB 2012

Conference

Conference2012 IEEE Symposium on Computational Intelligence and Computational Biology, CIBCB 2012
Country/TerritoryUnited States
CitySan Diego, CA
Period9/05/1212/05/12

Keywords

  • Attractors
  • Boolean networks
  • Gene regulatory networks
  • Robustness

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