common.bib

@comment{{Database of the Glasgow University  Centre for Systems and Control}}

@comment{{Abreviations for Journals }}

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@comment{{Database of publications by CSC in 1977 }}

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@comment{{Database of publications by CSC in 1978 }}

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@comment{{Database of publications by CSC in 1984 }}

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@comment{{Database of publications by CSC in 1988 }}

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@comment{{Database of publications by CSC in 1991 }}

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@article{GawCra14,
  author = {Gawthrop, Peter J. and Crampin, Edmund J.},
  title = {Energy-based analysis of biochemical cycles using bond graphs},
  volume = 470,
  number = 2171,
  year = 2014,
  doi = {10.1098/rspa.2014.0459},
  archiveprefix = {arXiv},
  eprint = {1406.2447},
  abstract = {Thermodynamic aspects of chemical reactions have a long history in the physical chemistry literature. In particular, biochemical cycles require a source of energy to function. However, although fundamental, the role of chemical potential and Gibb's free energy in the analysis of biochemical systems is often overlooked leading to models which are physically impossible. The bond graph approach was developed for modelling engineering systems, where energy generation, storage and transmission are fundamental. The method focuses on how power flows between components and how energy is stored, transmitted or dissipated within components. Based on the early ideas of network thermodynamics, we have applied this approach to biochemical systems to generate models which automatically obey the laws of thermodynamics. We illustrate the method with examples of biochemical cycles. We have found that thermodynamically compliant models of simple biochemical cycles can easily be developed using this approach. In particular, both stoichiometric information and simulation models can be developed directly from the bond graph. Furthermore, model reduction and approximation while retaining structural and thermodynamic properties is facilitated. Because the bond graph approach is also modular and scaleable, we believe that it provides a secure foundation for building thermodynamically compliant models of large biochemical networks.},
  journal = {Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science},
  pages = {1--25},
  note = {Available at {arXiv:1406.2447}}
}

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@article{GawCurCra15,
  author = {Gawthrop, Peter J. and Cursons, Joseph and Crampin, Edmund J.},
  title = {Hierarchical bond graph modelling of biochemical networks},
  volume = 471,
  number = 2184,
  year = 2015,
  doi = {10.1098/rspa.2015.0642},
  publisher = {The Royal Society},
  abstract = {The bond graph approach to modelling biochemical networks is extended to allow hierarchical construction of complex models from simpler components. This is made possible by representing the simpler components as thermodynamically open systems exchanging mass and energy via ports. A key feature of this approach is that the resultant models are robustly thermodynamically compliant: the thermodynamic compliance is not dependent on precise numerical values of parameters. Moreover, the models are reusable owing to the well-defined interface provided by the energy ports. To extract bond graph model parameters from parameters found in the literature, general and compact formulae are developed to relate free-energy constants and equilibrium constants. The existence and uniqueness of solutions is considered in terms of fundamental properties of stoichiometric matrices. The approach is illustrated by building a hierarchical bond graph model of glycogenolysis in skeletal muscle.},
  issn = {1364-5021},
  journal = {Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences},
  archiveprefix = {arXiv},
  eprint = {1503.01814},
  pages = {1--23},
  note = {Available at {arXiv:1503.01814}}
}

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@article{GawCra16,
  author = {P. J. Gawthrop and E. J. Crampin},
  journal = {IET Systems Biology},
  title = {Modular bond-graph modelling and analysis of biomolecular systems},
  year = 2016,
  volume = 10,
  number = 5,
  pages = {187-201},
  abstract = {Bond graphs can be used to build thermodynamically-compliant hierarchical models of biomolecular systems. As bond graphs have been widely used to model, analyse and synthesise engineering systems, this study suggests that they can play the same rôle in the modelling, analysis and synthesis of biomolecular systems. The particular structure of bond graphs arising from biomolecular systems is established and used to elucidate the relation between thermodynamically closed and open systems. Block diagram representations of the dynamics implied by these bond graphs are used to reveal implicit feedback structures and are linearised to allow the application of control-theoretical methods. Two concepts of modularity are examined: computational modularity where physical correctness is retained and behavioural modularity where module behaviour (such as ultrasensitivity) is retained. As well as providing computational modularity, bond graphs provide a natural formulation of behavioural modularity and reveal the sources of retroactivity. A bond graph approach to reducing retroactivity, and thus inter-module interaction, is shown to require a power supply such as that provided by the ATP ⇌ ADP + Pi reaction. The mitogen-activated protein kinase cascade (Raf-MEK-ERK pathway) is used as an illustrative example.},
  keywords = {biology computing;bond graphs;enzymes;hierarchical systems;molecular biophysics;physiological models;thermodynamics;ATP⇌ADP + Pi reaction;Michaelis-Menten kinetics;Raf-MEK-ERK pathway;behavioural modularity;biomolecular systems;block diagram representations;computational modularity;intermodule interaction;mitogen-activated protein kinase cascade;modular bond-graph modelling;retroactivity;signalling networks;thermodynamically-compliant hierarchical models},
  doi = {10.1049/iet-syb.2015.0083},
  issn = {1751-8849},
  month = {October},
  publisher = {Institution of Engineering and Technology},
  archiveprefix = {arXiv},
  eprint = {1511.06482},
  note = {Available at {arXiv:1511.06482}}
}

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@incollection{Gaw17,
  author = {Gawthrop, Peter J.},
  editor = {Borutzky, Wolfgang},
  title = {Bond-Graph Modelling and Causal Analysis of Biomolecular Systems},
  booktitle = {Bond Graphs for Modelling, Control and Fault Diagnosis of Engineering Systems},
  year = {2017},
  publisher = {Springer International Publishing},
  address = {Berlin},
  pages = {587--623},
  isbn = {978-3-319-47434-2},
  doi = {10.1007/978-3-319-47434-2_16},
  abstract = {Bond graph modelling of the biomolecular systems of living
                  organisms is introduced. Molecular species are
                  represented by non-linear C components and reactions
                  by non-linear two-port R components. As living
                  systems are neither at thermodynamic equilibrium nor
                  closed, open and non-equilibrium systems are
                  considered and illustrated using examples of
                  biomolecular systems. Open systems are modelled
                  using chemostats: chemical species with fixed
                  concentration. In addition to their role in ensuring
                  that models are energetically correct, bond graphs
                  provide a powerful and natural way of representing
                  and analysing causality. Causality is used in this
                  chapter to examine the properties of the junction
                  structures of biomolecular systems and how they
                  relate to biomolecular concepts.}
}

@article{Gaw17a,
  author = {P. J. Gawthrop},
  journal = {IEEE Transactions on NanoBioscience},
  title = {Bond Graph Modeling of Chemiosmotic Biomolecular Energy Transduction},
  year = 2017,
  volume = 16,
  number = 3,
  pages = {177-188},
  abstract = { Engineering systems modeling and analysis based on the bond
                  graph approach has been applied to biomolecular
                  systems. In this context, the notion of a
                  Faraday-equivalent chemical potential is introduced
                  which allows chemical potential to be expressed in
                  an analogous manner to electrical volts thus
                  allowing engineering intuition to be applied to
                  biomolecular systems. Redox reactions, and their
                  representation by half-reactions, are key components
                  of biological systems which involve both electrical
                  and chemical domains. A bond graph interpretation of
                  redox reactions is given which combines bond graphs
                  with the Faraday-equivalent chemical potential. This
                  approach is particularly relevant when the
                  biomolecular system implements chemoelectrical
                  transduction – for example chemiosmosis within the
                  key metabolic pathway of mitochondria: oxidative
                  phosphorylation. An alternative way of implementing
                  computational modularity using bond graphs is
                  introduced and used to give a physically based model
                  of the mitochondrial electron transport chain To
                  illustrate the overall approach, this model is
                  analyzed using the Faraday-equivalent chemical
                  potential approach and engineering intuition is used
                  to guide affinity equalisation: a energy based
                  analysis of the mitochondrial electron transport
                  chain.  },
  keywords = {Analytical models;Biological system modeling;Chemicals;Computational modeling;Context;Electric potential;Protons;Biological system modeling;computational systems biology;systems biology},
  doi = {10.1109/TNB.2017.2674683},
  issn = {1536-1241},
  month = {April},
  archiveprefix = {arXiv},
  eprint = {1611.04264},
  note = {Available at {arXiv:1611.04264}}
}

@article{GawCra17,
  author = {Gawthrop, Peter J. and Crampin, Edmund J.},
  title = {Energy-based analysis of biomolecular pathways},
  volume = 473,
  number = 2202,
  year = 2017,
  doi = {10.1098/rspa.2016.0825},
  publisher = {The Royal Society},
  archiveprefix = {arXiv},
  eprint = {1611.02332},
  note = {Available at {arXiv:1611.02332}},
  abstract = {Decomposition of biomolecular reaction networks into pathways is a powerful approach to the analysis of metabolic and signalling networks. Current approaches based on analysis of the stoichiometric matrix reveal information about steady-state mass flows (reaction rates) through the network. In this work, we show how pathway analysis of biomolecular networks can be extended using an energy-based approach to provide information about energy flows through the network. This energy-based approach is developed using the engineering-inspired bond graph methodology to represent biomolecular reaction networks. The approach is introduced using glycolysis as an exemplar; and is then applied to analyse the efficiency of free energy transduction in a biomolecular cycle model of a transporter protein [sodium-glucose transport protein 1 (SGLT1)]. The overall aim of our work is to present a framework for modelling and analysis of biomolecular reactions and processes which considers energy flows and losses as well as mass transport.},
  issn = {1364-5021},
  journal = {Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences}
}

@article{GawSieKam17,
  author = {P. J. Gawthrop and I. Siekmann and T. Kameneva and S. Saha and M. R. Ibbotson and E. J. Crampin},
  journal = {IET Systems Biology},
  title = {Bond graph modelling of chemoelectrical energy transduction},
  year = 2017,
  volume = 11,
  number = 5,
  pages = {127-138},
  abstract = {Energy-based bond graph modelling of biomolecular systems is extended to include chemoelectrical transduction thus enabling integrated thermodynamically compliant modelling of chemoelectrical systems in general and excitable membranes in particular. Our general approach is illustrated by recreating a well-known model of an excitable membrane. This model is used to investigate the energy consumed during a membrane action potential thus contributing to the current debate on the trade-off between the speed of an action potential event and energy consumption. The influx of Na+ is often taken as a proxy for energy consumption; in contrast, this study presents an energy-based model of action potentials. As the energy-based approach avoids the assumptions underlying the proxy approach it can be directly used to compute energy consumption in both healthy and diseased neurons. These results are illustrated by comparing the energy consumption of healthy and degenerative retinal ganglion cells using both simulated and in vitro data.},
  keywords = {biochemistry;bioelectric potentials;biomembrane transport;eye;molecular biophysics;neurophysiology;sodium;Na;biomolecular systems;chemoelectrical energy transduction;chemoelectrical systems;degenerative retinal ganglion cells;diseased neurons;energy consumption;energy-based bond graph modelling;excitable membranes;healthy neurons;healthy retinal ganglion cells;integrated thermodynamically compliant modelling;membrane action potential},
  doi = {10.1049/iet-syb.2017.0006},
  issn = {1751-8849},
  archiveprefix = {arXiv},
  eprint = {1512.00956},
  note = {Available at {arXiv:1512.00956}}
}

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@article{Gaw18,
  author = {P. Gawthrop},
  journal = {IEEE Transactions on NanoBioscience},
  title = {Computing Biomolecular System Steady-States},
  year = 2018,
  volume = 17,
  number = 1,
  pages = {36-43},
  abstract = {A new approach to compute the equilibria and the steady-states of biomolecular systems modeled by bond graphs is presented. The approach is illustrated using a model of a biomolecular cycle representing a membrane transporter and a model of the mitochondrial electron transport chain.},
  keywords = {Biological system modeling;Chemicals;Electric potential;Kinetic theory;Mathematical model;Nanobioscience;Steady-state;Biological system modeling;computational systems biology;systems biology},
  doi = {10.1109/TNB.2017.2787486},
  issn = {1536-1241},
  month = {March},
  note = {Published online 25th December 2017}
}

@inproceedings{GawCra18,
  author = {Peter J. Gawthrop and Edmund J. Crampin},
  title = {Biomolecular System Energetics},
  booktitle = {Proceedings of the 13th International Conference on Bond Graph Modeling ({ICBGM'18})},
  publisher = {Society for Computer Simulation},
  year = 2018,
  address = {Bordeaux},
  archiveprefix = {arXiv},
  eprint = {1803.09231},
  note = {Available at {arXiv:1803.09231}},
  abstract = {Efficient energy transduction is one driver of evolution;
                  and thus understanding biomolecular energy
                  transduction is crucial to understanding living
                  organisms. As an energy-orientated modelling
                  methodology, bond graphs provide a useful approach
                  to describing and modelling the efficiency of living
                  systems. This paper gives some new results on the
                  efficiency of metabolism based on bond graph models
                  of the key metabolic processes: glycolysis.}
}

@article{PanGawTra18,
  author = {Pan, Michael and Gawthrop, Peter J. and Tran, Kenneth and Cursons, Joseph and Crampin, Edmund J.},
  title = {Bond graph modelling of the~cardiac action potential: implications for drift and non-unique steady states},
  volume = 474,
  number = 2214,
  year = 2018,
  doi = {10.1098/rspa.2018.0106},
  publisher = {The Royal Society},
  abstract = {Mathematical models of cardiac action potentials have become increasingly important in the study of heart disease and pharmacology, but concerns linger over their robustness during long periods of simulation, in particular due to issues such as model drift and non-unique steady states. Previous studies have linked these to violation of conservation laws, but only explored those issues with respect to charge conservation in specific models. Here, we propose a general and systematic method of identifying conservation laws hidden in models of cardiac electrophysiology by using bond graphs, and develop a bond graph model of the cardiac action potential to study long-term behaviour. Bond graphs provide an explicit energy-based framework for modelling physical systems, which makes them well suited for examining conservation within electrophysiological models. We find that the charge conservation laws derived in previous studies are examples of the more general concept of a {\textquoteleft}conserved moiety{\textquoteright}. Conserved moieties explain model drift and non-unique steady states, generalizing the results from previous studies. The bond graph approach provides a rigorous method to check for drift and non-unique steady states in a wide range of cardiac action potential models, and can be extended to examine behaviours of other excitable systems.},
  issn = {1364-5021},
  journal = {Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences},
  archiveprefix = {arXiv},
  eprint = {1802.04548},
  note = {Available at {arXiv:1802.04548}}
}

@article{GawCra18a,
  author = {P. Gawthrop and E. J. Crampin},
  journal = {IEEE Transactions on NanoBioscience},
  title = {Bond Graph Representation of Chemical Reaction Networks},
  year = 2018,
  pages = {449-455},
  volume = 17,
  number = 4,
  month = {October},
  abstract = {The Bond Graph approach and the Chemical Reaction Network approach to modelling biomolecular systems developed independently. This paper brings together the two approaches by providing a bond graph interpretation of the chemical reaction network concept of complexes. Both closed and open systems are discussed. The method is illustrated using a simple enzyme-catalysed reaction and a trans-membrane transporter.},
  keywords = {Chemicals;Junctions;Substrates;Standards;Nanobioscience;Biological system modeling;Open systems},
  doi = {10.1109/TNB.2018.2876391},
  issn = {1536-1241},
  archiveprefix = {arXiv},
  eprint = {1809.00449},
  note = {Available at {arXiv:1809.00449}}
}

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@article{PanGawTra19,
  title = {A thermodynamic framework for modelling membrane transporters},
  journal = {Journal of Theoretical Biology},
  volume = 481,
  pages = {10 - 23},
  year = 2019,
  issn = {0022-5193},
  doi = {10.1016/j.jtbi.2018.09.034},
  author = {Michael Pan and Peter J. Gawthrop and Kenneth Tran and Joseph Cursons and Edmund J. Crampin},
  keywords = {Bond graph, Biochemistry, Chemical reaction network, Biomedical engineering, Systems biology},
  abstract = {Membrane transporters contribute to the regulation of the internal environment of cells by translocating substrates across cell membranes. Like all physical systems, the behaviour of membrane transporters is constrained by the laws of thermodynamics. However, many mathematical models of transporters, especially those incorporated into whole-cell models, are not thermodynamically consistent, leading to unrealistic behaviour. In this paper we use a physics-based modelling framework, in which the transfer of energy is explicitly accounted for, to develop thermodynamically consistent models of transporters. We then apply this methodology to model two specific transporters: the cardiac sarcoplasmic/endoplasmic Ca2+ ATPase (SERCA) and the cardiac Na+/K+ ATPase.},
  archiveprefix = {arXiv},
  eprint = {1806.04341},
  note = {Available at {arXiv:1806.04341}}
}

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@article{GawCudCra20,
  title = {Physically-Plausible Modelling of Biomolecular Systems: A Simplified, Energy-Based Model of the Mitochondrial Electron Transport Chain},
  journal = {Journal of Theoretical Biology},
  pages = 110223,
  volume = 493,
  year = 2020,
  issn = {0022-5193},
  doi = {10.1016/j.jtbi.2020.110223},
  author = {Peter J. Gawthrop and Peter Cudmore and Edmund J. Crampin},
  keywords = {Systems biology, Thermodynamical modelling, Bond graph, Computational biology},
  abstract = {Advances in systems biology and whole-cell modelling demand increasingly comprehensive mathematical models of cellular biochemistry. Such models require the development of simplified representations of specific processes which capture essential biophysical features but without unnecessarily complexity. Recently there has been renewed interest in thermodynamically-based modelling of cellular processes. Here we present an approach to developing of simplified yet thermodynamically consistent (hence physically plausible) models which can readily be
                  incorporated into large scale biochemical
                  descriptions but which do not require full
                  mechanistic detail of the underlying processes. We
                  illustrate the approach through development of a simplified, physically plausible model of the mitochondrial electron transport chain and show that the simplified model behaves like the full system.}
}

@article{PanGawCur20,
  author = {Michael Pan and Peter J. Gawthrop and Joseph Cursons and Kenneth Tran and Edmund J. Crampin},
  title = {{The cardiac Na+/K+ ATPase: An updated, thermodynamically consistent model}},
  year = 2020,
  month = 8,
  journal = {Physiome},
  doi = {10.36903/physiome.12871070.v1},
  abstract = {
The Na+/K+ATPase is an essential component of cardiac electrophysiology, maintaining physiological Na+ and K+ concentrations over successive heart beats. Terkildsen et al. (2007) developed a model of the ventricular myocyte Na+/K+ ATPase to study extracellular potassium accumulation during ischaemia, demonstrating the ability to recapitulate a wide range of experimental data, but unfortunately there was no archived code associated with the original manuscript. Here we detail an updated version of the model and provide CellML and MATLAB code to ensure reproducibility and reusability. We note some errors within the original formulation which have been corrected to ensure that the model is thermodynamically consistent, and although this required some reparameterisation, the resulting model still provides a good fit to experimental measurements that demonstrate the dependence of Na+/K+ ATPase pumping rate upon membrane voltage and metabolite concentrations. To demonstrate thermodynamic consistency we also developed a bond graph version of the model. We hope that these models will be useful for community efforts to assemble a whole-cell cardiomyocyte model which facilitates the investigation of cellular energetics.
}
}

@article{GawPan20,
  author = {Gawthrop, Peter J.
		and Pan, Michael},
  title = {Network Thermodynamical Modeling of Bioelectrical Systems: A Bond Graph Approach},
  journal = {Bioelectricity},
  year = 2021,
  month = {Mar},
  day = 01,
  publisher = {Mary Ann Liebert, Inc., publishers},
  volume = 3,
  number = 1,
  pages = {3--13},
  abstract = {Interactions among biomolecules, electrons, and protons are essential to many fundamental processes sustaining life. It is therefore of interest to build mathematical models of these bioelectrical processes not only to enhance understanding but also to enable computer models to complement in vitro and in vivo experiments. Such models can never be entirely accurate; it is nevertheless important that the models are compatible with physical principles. Network Thermodynamics, as implemented with bond graphs, provide one approach to creating physically compatible mathematical models of bioelectrical systems. This is illustrated using simple models of ion channels, redox reactions, proton pumps, and electrogenic membrane transporters thus demonstrating that the approach can be used to build mathematical and computer models of a wide range of bioelectrical systems.},
  issn = {2576-3105},
  doi = {10.1089/bioe.2020.0042},
  note = {Published Online: 18 Dec 2020}
}

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@article{Gaw21,
  author = {P. J. {Gawthrop}},
  journal = {IEEE Transactions on NanoBioscience},
  title = {Energy-Based Modeling of the Feedback Control of Biomolecular Systems With Cyclic Flow Modulation},
  year = 2021,
  volume = 20,
  number = 2,
  pages = {183-192},
  abstract = {Energy-based modelling brings engineering insight to the understanding of biomolecular systems. It is shown how well-established control engineering concepts, such as loop-gain, arise from energy feedback loops and are therefore amenable to control engineering insight. In particular, a novel method is introduced to allow the transfer function based approach of classical linear control to be utilised in the analysis of feedback systems modelled by network thermodynamics and thus amalgamate energy-based modelling with control systems analysis. The approach is illustrated using a class of metabolic cycles with activation and inhibition leading to the concept of Cyclic Flow Modulation.},
  keywords = {Biological system modeling;Junctions;Transfer functions;Thermodynamics;Mathematical model;Feedback loop;Analytical models;Biological system modeling;computational systems biology;systems biology;negative feedback},
  doi = {10.1109/TNB.2021.3058440},
  issn = {1558-2639},
  month = {April}
}

@article{GawPanCra21,
  author = {Gawthrop, Peter J.  and Pan, Michael  and Crampin, Edmund J. },
  title = {Modular dynamic biomolecular modelling with bond graphs: the unification of stoichiometry, thermodynamics, kinetics and data},
  journal = {Journal of The Royal Society Interface},
  volume = 18,
  number = 181,
  pages = 20210478,
  year = 2021,
  doi = {10.1098/rsif.2021.0478},
  abstract = { Renewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here, we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermodynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of Escherichia coli and published experimental data. }
}

@article{PanGawCurCra21,
  author = {Pan, Michael
		and Gawthrop, Peter J.
		and Cursons, Joseph
		and Crampin, Edmund J.},
  title = {Modular assembly of dynamic models in systems biology},
  journal = {PLOS Computational Biology},
  year = 2021,
  month = {Oct},
  day = 13,
  publisher = {Public Library of Science},
  volume = 17,
  number = 10,
  pages = {e1009513},
  abstract = {Author summary The biochemistry within a cell is complex, being composed of numerous biomolecules and reactions. In order to develop fully detailed mathematical models of cells, smaller submodels need to be constructed and connected together. Software and standards can assist in this endeavour, but challenges remain in ensuring that submodels are both consistent with each other and consistent with the fundamental conservation laws of physics. In this paper, we propose a new approach using bond graphs from engineering. In this approach, connections between models are defined using physical conservation laws. We show that this approach is compatible with current software approaches in the field, and can therefore be readily used to incorporate physical consistency into existing model integration methodologies. We illustrate the utility of this approach in streamlining the development of models for a signalling network (the MAPK cascade) and a metabolic network (the glycolysis pathway). The advantage of this approach is that models can be developed in a scalable manner while also ensuring consistency with the laws of physics, enhancing the range of data available to train models. This approach can be used to quickly construct detailed and accurate models of cells, facilitating future advances in biotechnology and personalised medicine.},
  doi = {10.1371/journal.pcbi.1009513}
}

@article{CudPanGaw21,
  author = {Cudmore, Peter
		and Pan, Michael
		and Gawthrop, Peter J.
		and Crampin, Edmund J.},
  title = {Analysing and simulating energy-based models in biology using {BondGraphTools}},
  journal = {The European Physical Journal E},
  year = 2021,
  month = {Dec},
  day = 13,
  volume = 44,
  number = 12,
  pages = 148,
  abstract = {Like all physical systems, biological systems are constrained by the laws of physics. However, mathematical models of biochemistry frequently neglect the conservation of energy, leading to unrealistic behaviour. Energy-based models that are consistent with conservation of mass, charge and energy have the potential to aid the understanding of complex interactions between biological components, and are becoming easier to develop with recent advances in experimental measurements and databases. In this paper, we motivate the use of bond graphs (a modelling tool from engineering) for energy-based modelling and introduce, BondGraphTools, a Python library for constructing and analysing bond graph models. We use examples from biochemistry to illustrate how BondGraphTools can be used to automate model construction in systems biology while maintaining consistency with the laws of physics.},
  issn = {1292-895X},
  doi = {10.1140/epje/s10189-021-00152-4}
}

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@article{GawPan22,
  title = {Network thermodynamics of biological systems: A bond graph approach},
  journal = {Mathematical Biosciences},
  volume = 352,
  pages = 108899,
  year = 2022,
  issn = {0025-5564},
  doi = {https://doi.org/10.1016/j.mbs.2022.108899},
  author = {Peter J. Gawthrop and Michael Pan},
  keywords = {Systems biology, Bond graph, Energy-based, Photosynthesis, Electrochemical transduction},
  abstract = {Edmund Crampin (1973-2021) was at the forefront of Systems Biology research and his work will influence the field for years to come. This paper brings together and summarises the seminal work of his group in applying energy-based bond graph methods to biological systems. In particular, this paper: (a) motivates the need to consider energy in modelling biology; (b) introduces bond graphs as a methodology for achieving this; (c) describes extensions to modelling electrochemical transduction; (d) outlines how bond graph models can be constructed in a modular manner and (e) describes stoichiometric approaches to deriving fundamental properties of reaction networks. These concepts are illustrated using a new bond graph model of photosynthesis in chloroplasts.}
}

@article{GawPan22a,
  author = {Gawthrop, Peter J.  and Pan, Michael },
  title = {Energy-based advection modelling using bond graphs},
  journal = {Journal of The Royal Society Interface},
  volume = 19,
  number = 195,
  pages = 20220492,
  year = 2022,
  doi = {10.1098/rsif.2022.0492},
  abstract = { Advection, the transport of a substance by the flow of a fluid, is a key process in biological systems. The energy-based bond graph approach to modelling chemical transformation within reaction networks is extended to include transport and thus advection. The approach is illustrated using a simple model of advection via circulating flow and by a simple pharmacokinetic model of anaesthetic gas uptake. This extension provides a physically consistent framework for linking advective flows with the fluxes associated with chemical reactions within the context of physiological systems in general and the human physiome in particular. }
}

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@article{GawPan23,
  author = {Gawthrop, Peter J.  and Pan, Michael },
  title = {Sensitivity analysis of biochemical systems using bond graphs},
  journal = {Journal of The Royal Society Interface},
  volume = 20,
  number = 204,
  pages = 20230192,
  year = 2023,
  doi = {10.1098/rsif.2023.0192},
  abstract = { The sensitivity of systems biology models to parameter variation can give insights into which parameters are most important for physiological function, and also direct efforts to estimate parameters. However, in general, kinetic models of biochemical systems do not remain thermodynamically consistent after perturbing parameters. To address this issue, we analyse the sensitivity of biological reaction networks in the context of a bond graph representation. We find that the parameter sensitivities can themselves be represented as bond graph components, mirroring potential mechanisms for controlling biochemistry. In particular, a sensitivity system is derived which re-expresses parameter variation as additional system inputs. The sensitivity system is then linearized with respect to these new inputs to derive a linear system which can be used to give local sensitivity to parameters in terms of linear system properties such as gain and time constant. This linear system can also be used to find so-called sloppy parameters in biological models. We verify our approach using a model of the Pentose Phosphate Pathway, confirming the reactions and metabolites most essential to maintaining the function of the pathway. }
}

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@article{GawPanRaj25,
  author = {Gawthrop, Peter J.  and Pan, Michael  and Rajagopal, Vijay },
  title = {Energy-based modelling of single actin filament polymerization using bond graphs},
  journal = {Journal of The Royal Society Interface},
  volume = 22,
  number = 222,
  pages = 20240404,
  year = 2025,
  doi = {10.1098/rsif.2024.0404},
  abstract = { Bond graphs provide an energy-based methodology for modelling complex systems hierarchically; at the moment, the method allows biological systems with both chemical and electrical subsystems to be modelled. Herein, the bond graph approach is extended to include chemomechanical transduction thus extending the range of biological systems to be modelled. Actin filament polymerization and force generation is used as an example of chemomechanical transduction, and 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 and Mogilner. Furthermore, it is shown that the bond graph approach leads to the same equation as the Brownian ratchet approach in the simplest case. The approach is illustrated by showing that flexibility and non-normal incidence can be modelled by simply adding additional bond graph components and that compliance leads to non-convexity of the force–velocity curve. Energy flows are fundamental to life; for this reason, the energy-based approach is utilized to investigate the power transmission by the actin filament and its corresponding efficiency. The bond graph model is fitted to experimental data by adjusting the model physical parameters. }
}

@article{GawPan25,
  author = {Gawthrop, Peter  and Pan, Michael },
  title = {Energy-based analysis of biochemical oscillators using bond graphs and linear control theory},
  journal = {Royal Society Open Science},
  volume = 12,
  number = 4,
  pages = 241791,
  year = 2025,
  doi = {10.1098/rsos.241791},
  abstract = { The bond graph approach has been recognized as a useful conceptual basis for understanding the behaviour of living entities modelled as a system with hierarchical interacting parts exchanging energy. One such behaviour is oscillation, which underpins many essential biological functions. 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 formalized 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’kov model of glycolytic oscillations and the repressilator. }
}

@article{PanGawFar25,
  author = {Pan, Michael  and Gawthrop, Peter J.  and Faria, Matthew  and Johnston, Stuart T. },
  title = {Thermodynamically consistent, reduced models of gene regulatory networks},
  journal = {Royal Society Open Science},
  volume = 12,
  number = 7,
  pages = 241725,
  year = 2025,
  doi = {10.1098/rsos.241725},
  abstract = { Synthetic biology aims to engineer novel functionalities
                  into biological systems. While the approach has 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, a modelling
                  approach that ensures thermodynamic consistency. Our
                  reduced model is significantly faster to simulate
                  than the full model and 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 here are a bridge
                  towards engineering collective cell behaviours such
                  as synchronization and division of labour.
		  }
}

@article{MalGugHun25,
  author = {Malecki, Cassandra and Guglielmi, Giovanni and Hunter, Benjamin and Harney, Dylan and Koay, Yen Chin and Don, Anthony. S. and Han, Oscar and Khor, Jasmine and Nguyen, Lisa and Pan, Michael and Gawthrop, Peter and Isles, Nathan and Chung, Joshua and Hume, Robert. D. and Taper, Matthew and Wang, XiaoSuo and Larance, Mark and Spill, Fabian and Rajagopal, Vijay and O'Sullivan, John F. and Lal, Sean},
  title = {The Human Cardiac "Age-OME": Age-Specific Changes in Myocardial Molecular Expression},
  journal = {Aging Cell},
  volume = {n/a},
  number = {n/a},
  year = 2025,
  pages = {e70219},
  keywords = {ageing, age-OME, excitation-contraction coupling, human heart, metabolism, omics},
  doi = {https://doi.org/10.1111/acel.70219},
  note = {e70219 ACE-24-1128-RAr},
  abstract = {Ageing is one of the most significant risk factors for heart disease; however, it is still not clear how the human heart changes with age. Taking advantage of a unique set of pre-mortem, cryopreserved, non-diseased human hearts, we performed omics analyses (transcriptomics, proteomics, metabolomics, and lipidomics), coupled with biologically informed computational modelling in younger (<25~years~old) and older hearts (>50~years~old) to describe the molecular landscape of human cardiac ageing. In older hearts, we observed a downregulation of proteins involved in calcium signalling and the contractile apparatus. Furthermore, we found a potential dysregulation of central carbon generation of fuel, glycolysis, and fatty acids oxidation, along with an increase in long-chain fatty acids. This study presents and analyses the first molecular data set of normal human cardiac ageing, which has relevant implications for understanding the human cardiac ageing process and the development of age-related heart disease.}
}

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	Control Group}}

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@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 1995 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 1996 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 1997 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 1998 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 1999 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2000 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2001 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2002 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2003 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2004 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2005 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2006 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2007 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2008 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2009 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2010 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2011 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2012 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2013 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2014 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2015 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2016 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2017 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2018 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2019 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2018 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2020 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2021 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2022 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2023 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set Emacs into bibtex-mode}}

@comment{{Database of non-CSC publications  in 2024 }}

@comment{{This is the file that should be edited to add non-CSC publications}}

@comment{{-*-bibtex-*- used to set EMACS into bibtex-mode}}

@comment{{Cross References for Conferences MUST go in footers}}

This file was generated by bibtex2html 1.99.