Equilibrium switching in nonlinear biological interaction networks with concurrent antagonism
- Published
- Accepted
- Subject Areas
- Bioinformatics, Biophysics, Computational Biology, Mathematical Biology, Computational Science
- Keywords
- biological switch, regulatory network, species competition, sigmoid kinetics, multi-stability, repressilator, perception
- Copyright
- © 2014 Rabajante et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2014. Equilibrium switching in nonlinear biological interaction networks with concurrent antagonism. PeerJ PrePrints 2:e382v2 https://doi.org/10.7287/peerj.preprints.382v2
Abstract
Concurrent decision-making model (CDM) of interaction networks involving more than two antagonistic components can represent various biological systems, such as gene interaction, species competition and mental perception. The model assumes sigmoid kinetics where every component stimulates itself but concurrently represses the others. Here we prove general dynamical properties of the CDM (e.g., location and stability of steady states) for any dimension of the state space even if the reciprocal antagonism between two components is asymmetric. Significant modifications in parameter values serve as biological regulators for inducing steady state switching by leading a temporal state to escape an undesired equilibrium. Increasing the maximal growth rate and decreasing the decay rate expand the basin of attraction of a steady state with the desired dominant component. Perpetually adding an external stimulus can shut down multi-stability of the system that increases the robustness of the system against stochastic noise. We further show that asymmetric interaction that forms a repressilator-type network generates oscillatory behavior.
Author Comment
This is an early version of the manuscript (not yet peer reviewed). In this preprint revision, we updated the abstract and some information, such as authorship.