Super-transient scaling in time-delay autonomous Boolean network motifs

Abstract

Autonomous Boolean networks are commonly used to model the dynamics of gene regulatory networks and allow for the prediction of stable dynamical attractors. However, most models do not account for time delays along the network links and noise, which are crucial features of real biological systems. Concentrating on two paradigmatic motifs, the toggle switch and the repressilator, we develop an experimental testbed that explicitly includes both inter-node time delays and noise using digital logic elements on field-programmable gate arrays. We observe transients that last millions to billions of characteristic time scales and scale exponentially with the amount of time delays between nodes, a phenomenon known as super-transient scaling. We develop a hybrid model that includes time delays along network links and allows for stochastic variation in the delays. Using this model, we explain the observed super-transient scaling of both motifs and recreate the experi- mentally measured transient distributions.

Publication DOI: https://doi.org/10.1063/1.4954274
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT)
Publication ISSN: 1089-7682
Last Modified: 30 Oct 2024 08:24
Date Deposited: 13 Feb 2018 14:56
PURE Output Type: Article
Published Date: 2016-07-01
Accepted Date: 2016-05-01
Authors: D'Huys, Otti (ORCID Profile 0000-0001-7498-6771)
Lohmann, Johannes
Haynes, Nicholas D.
Gauthier, Daniel J.

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