In this section
@article{Pazuki:2024:10.1103/PhysRevE.109.064305,
author = {Pazuki, RH and Endres, RG},
doi = {10.1103/PhysRevE.109.064305},
journal = {Physical review E (statistical, nonlinear, biological, and soft matter physics)},
title = {Robustness of Turing models and gene regulatory networks with a sweet spot},
url = {http://dx.doi.org/10.1103/PhysRevE.109.064305},
volume = {109},
year = {2024}
}
TY - JOUR
AB - Traditional linear stability analysis based on matrix diagonalization is a computationally intensive process for high-dimensional systems of differential equations, posing substantial limitations for the exploration of Turing systems of pattern formation where an additional wave-number parameter needs to be investigated. In this paper, we introduce an efficient and intuitive technique that leverages Gershgorin's theorem to determine upper limits on regions of parameter space and the wave number beyond which Turing instabilities cannot occur. This method offers a streamlined avenue for exploring the phase diagrams of other complex multi-parametric models, such as those found in gene regulatory networks in systems biology. Due to its suitability for the asymptotic limit of infinitely large systems, it predicts the existence of a sweet spot in network size for maximal Jacobian stability.
AU - Pazuki,RH
AU - Endres,RG
DO - 10.1103/PhysRevE.109.064305
PY - 2024///
SN - 2470-0045
TI - Robustness of Turing models and gene regulatory networks with a sweet spot
T2 - Physical review E (statistical, nonlinear, biological, and soft matter physics)
UR - http://dx.doi.org/10.1103/PhysRevE.109.064305
UR - https://journals.aps.org/pre/abstract/10.1103/PhysRevE.109.064305
UR - http://hdl.handle.net/10044/1/112348
VL - 109
ER -
Interested in studying a PhD at the Department of Life Sciences? Find out more about postgraduate research opportunties.