A method of ‘speed coefficients’ for biochemical model reduction applied to the NF-κB system.
Biktashev, V. N.
Journal of Mathematical Biology
© The Author(s) 2014. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
The relationship between components of biochemical network and the resulting dynamics of the overall system is a key focus of computational biology. However, as these networks and resulting mathematical models are inherently complex and non-linear, the understanding of this relationship becomes challenging. Among many approaches, model reduction methods provide an avenue to extract components responsible for the key dynamical features of the system. Unfortunately, these approaches often require intuition to apply. In this manuscript we propose a practical algorithm for the reduction of biochemical reaction systems using fast-slow asymptotics. This method allows the ranking of system variables according to how quickly they approach their momentary steady state, thus selecting the fastest for a steady state approximation. We applied this method to derive models of the Nuclear Factor kappa B network, a key regulator of the immune response that exhibits oscillatory dynamics. Analyses with respect to two specific solutions, which corresponded to different experimental conditions identified different components of the system that were responsible for the respective dynamics. This is an important demonstration of how reduction methods that provide approximations around a specific steady state, could be utilised in order to gain a better understanding of network topology in a broader context.
Biotechnology and Biological Sciences Research Council (BBSRC)
BBSRC David Phillips Research Fellowship
This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.
Journal of Mathematical Biology, 2014, Vol. 70 (3), pp. 591 - 620
Place of publication