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Complex and unexpected dynamics in simple genetic regulatory networks

Borg, Y; Ullner, E; Alagha, A; Alsaedi, A; Nesbeth, D; Zaikin, A; (2014) Complex and unexpected dynamics in simple genetic regulatory networks. INTERNATIONAL JOURNAL OF MODERN PHYSICS B , 28 (14) , Article ARTN 1430006. 10.1142/S0217979214300060. Green open access

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Abstract

One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.

Type: Article
Title: Complex and unexpected dynamics in simple genetic regulatory networks
Open access status: An open access version is available from UCL Discovery
DOI: 10.1142/S0217979214300060
Publisher version: http://dx.doi.org/10.1142/S0217979214300060
Additional information: © The Authors. This is an Open Access article published byWorld Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 3.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited.
Keywords: Synthetic biology, genetic regulatory networks, complex dynamics, mathematical modeling, repressilator, artificial cell differentiation, synchronization, noise, cellular decision making
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health > Womens Cancer
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Biochemical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/1425978
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