Preprint Open Access

Exploring the Dynamics of Nonlinear Biochemical Systems using Control-Based Continuation

Gomes, Brandon; de Cesare, Irene; Guarino, Agostino; di Bernardo, Mario; Renson, Ludovic; Marucci, Lucia


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    <subfield code="u">Department of Electrical Engineering and Information Technology, University of Naples, Naples 80125 Naples, Italy</subfield>
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    <subfield code="u">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</subfield>
    <subfield code="a">di Bernardo, Mario</subfield>
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    <subfield code="u">Engineering Mathematics Department, University of Bristol, Bristol BS8 1UB, UK</subfield>
    <subfield code="a">Renson, Ludovic</subfield>
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    <subfield code="u">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</subfield>
    <subfield code="a">Marucci, Lucia</subfield>
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    <subfield code="u">Engineering Mathematics Department, University of Bristol, Bristol BS8 1UB, UK</subfield>
    <subfield code="a">Gomes, Brandon</subfield>
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    <subfield code="a">Exploring the Dynamics of Nonlinear Biochemical Systems using Control-Based Continuation</subfield>
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    <subfield code="a">&lt;p&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;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.&lt;/p&gt;

&lt;p&gt;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.&lt;/p&gt;

&lt;p&gt;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.&lt;/p&gt;</subfield>
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    <subfield code="a">10.1101/695866</subfield>
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