Exploring the Dynamics of Nonlinear Biochemical Systems using Control-Based Continuation
Creators
- 1. Engineering Mathematics Department, University of Bristol, Bristol BS8 1UB, UK
- 2. Department of Electrical Engineering and Information Technology, University of Naples, Naples 80125 Naples, Italy
- 3. Engineering Mathematics Department, University of Bristol, Bristol BS8 1UB, UK - Department of Electrical Engineering and Information Technology, University of Naples, Naples 80125 Naples, Italy - Bristol Centre for Synthetic Biology, University of Bristol, Life Sciences Building Tyndall Avenue, Bristol, BS8 1TQ, UK
- 4. Engineering Mathematics Department, University of Bristol, Bristol BS8 1UB, UK - Bristol Centre for Synthetic Biology, University of Bristol, Life Sciences Building Tyndall Avenue, Bristol, BS8 1TQ, UK
Description
Abstract
Mathematical modelling is routinely used in Systems Biology to understand the mechanisms causing nonlinear phenomena in gene expression, such as switch-like behaviours and temporal oscillations. The reliability of model predictions and bifurcation analysis depend on modelling assumptions and specific choices of model parameters; however, the identification of models is highly challenging due to the complexity of biochemical interactions and noise in experimental data.
This paper numerically investigates the use of control-based continuation (CBC) for tracking dynamical features of biochemical systems and, in particular, the bistable dynamics of a gene regulating pluripotency in embryonic stem cells.
CBC is a method that exploits feedback control and path following algorithms to explore the dynamic features of a nonlinear physical system directly during experimental tests. CBC applications have so far been limited to non-living (i.e. electro-mechanical) systems. Our numerical simulations show that, in principle, CBC could also be applied to biological experiments to characterise the switch-like dynamics of genes that are important for cell decision making.
Files
Gomes et al 2018 biorxiv.pdf
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(265.6 kB)
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