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Boolean networks with robust and reliable trajectories

Schmal, Christoph ; Peixoto, Tiago P. ; Drossel, Barbara (2024)
Boolean networks with robust and reliable trajectories.
In: New Journal of Physics, 2010, 12 (11)
doi: 10.26083/tuprints-00020561
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Boolean networks with robust and reliable trajectories
Language: English
Date: 5 March 2024
Place of Publication: Darmstadt
Year of primary publication: 30 November 2010
Place of primary publication: London
Publisher: IOP Publishing
Journal or Publication Title: New Journal of Physics
Volume of the journal: 12
Issue Number: 11
Collation: 13 Seiten
DOI: 10.26083/tuprints-00020561
Corresponding Links:
Origin: Secondary publication DeepGreen
Abstract:

We construct and investigate Boolean networks that follow a given reliable trajectory in state space, which is insensitive to fluctuations in the updating schedule and which is also robust against noise. Robustness is quantified as the probability that the dynamics return to the reliable trajectory after a perturbation of the state of a single node. In order to achieve high robustness, we navigate through the space of possible update functions by using an evolutionary algorithm. We constrain the networks to those having the minimum number of connections required to obtain the reliable trajectory. Surprisingly, we find that robustness always reaches values close to 100% during the evolutionary optimization process. The set of update functions can be evolved such that it differs only slightly from that of networks that were not optimized with respect to robustness. The state space of the optimized networks is dominated by the basin of attraction of the reliable trajectory.

Identification Number: Artikel-ID: 113054
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-205610
Classification DDC: 500 Science and mathematics > 530 Physics
Divisions: 05 Department of Physics > Institute for Condensed Matter Physics
Date Deposited: 05 Mar 2024 10:13
Last Modified: 27 May 2024 07:19
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/20561
PPN: 518578968
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