@article{GawPan24X,
author = {Gawthrop, Peter J. and Pan, Michael},
title = {Energy-based Analysis of Biochemical Oscillators Using Bond Graphs and Linear Control Theory},
elocation-id = {2024.06.06.597695},
year = 2024,
doi = {10.1101/2024.06.06.597695},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Oscillatory behaviour underpins many essential biological functions and energy is required to sustain oscillation. In this paper, energy-based modelling of biochemical systems using the bond graph approach is combined with classical feedback control theory to give a novel approach to the analysis, and potentially synthesis, of biochemical oscillators. It is shown that oscillation is dependent on the interplay between active and passive feedback and this interplay is formalised using classical frequency-response analysis of feedback systems. In particular, the phase margin is suggested as a simple scalar indicator of the presence or absence of oscillations; it is shown how this indicator can be used to investigate the effect of both the structure and parameters of biochemical system on oscillation. It follows that the combination of classical feedback control theory and the bond graph approach to systems biology gives a novel analysis and design methodology for biochemical oscillators.The approach is illustrated using an introductory example similar to the Goodwin oscillator, the Sel{extquoteright}kov model of Glycolytic Oscillations and the Repressilator.Competing Interest StatementThe authors have declared no competing interest.},
journal = {bioRxiv}
}
@article{GawPanRaj24X,
author = {Gawthrop, Peter J. and Pan, Michael and Rajagopal, Vijay},
title = {Energy-based Modelling of Single Actin Filament Polymerisation Using Bond Graphs},
elocation-id = {2024.06.14.598965},
year = 2024,
doi = {10.1101/2024.06.14.598965},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Energy-based modelling of single actin filament polymerisation and force generation is investigated using the bond graph approach. It is shown that the TF (transformer) bond graph component provides a practical, and conceptually simple, alternative to the Brownian ratchet approach of Peskin, Odell, Oster amp; Mogilner. Three cases are examined: rigid filament normal to a surface; rigid filament at an angle to a surface and a flexible filament. The latter two cases correspond to incremental additions to the bond graph of the first case. In the first case, the explicit formula derived from the bond graph is identical to that derived by the Brownian ratchet approach. Energy flows are fundamental life; for this reason, the energy based approach is utilised to investigate the power transmission by the actin filament and its corresponding efficiency.The bond graph model is fitted to experimental data by adjusting model physical parameters.Competing Interest StatementThe authors have declared no competing interest.},
journal = {bioRxiv}
}
@article{PanGawFarJoh24X,
author = {Pan, Michael and Gawthrop, Peter J. and Faria, Matthew and Johnston, Stuart T.},
title = {Thermodynamically-consistent, reduced models of gene regulatory networks},
elocation-id = {2023.11.13.566770},
year = 2024,
doi = {10.1101/2023.11.13.566770},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Synthetic biology aims to engineer novel functionalities into biological systems. While the approach has to date been predominantly applied to single cells, a richer set of biological phenomena can be engineered by applying synthetic biology to cell populations. To rationally design cell populations, we require mathematical models that link between intracellular biochemistry and intercellular interactions. In this study, we develop a kinetic model of gene expression that is suitable for incorporation into agent-based models of cell populations. To be scalable to large cell populations, models of gene expression should be both computationally efficient and compliant with the laws of physics. We satisfy the first requirement by applying a model reduction scheme to translation, and the second requirement by formulating models using bond graphs. Our reduced model is significantly faster to simulate than the full model, and faithfully reproduces important behaviours of the full model. We couple separate models of gene expression to build models of the toggle switch and repressilator. With these models, we explore the effects of resource availability and cell-to-cell heterogeneity on circuit behaviour. The modelling approaches developed in this study are a bridge towards engineering collective cell behaviours such as synchronisation and division of labour.Competing Interest StatementThe authors have declared no competing interest.},
journal = {bioRxiv}
}
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