Welcome to the Systems Biology Laboratory at the University of Melbourne, Australia.
We develop biophysically-based mathematical models of biological processes, pathways and networks, and we apply these models to problems in medicine and biotechnology including heart disease, cancer, nanomedicine and synthetic biology.
Congratulations to Dr Matt Faria, who has been awarded an Emerging Research Leader award at the final research workshop of the ARC Centre of Excellence in Convergent Bio-Nano Science and Technology (CBNS)!
Many congratulations to Hilary, who has completed her PhD.
Hilary’s thesis ‘Mathematical models of calcium signalling in the context of cardiac hypertrophy’ was supervised by Prof. Edmund Crampin and Dr Vijay Rajagopal, with Prof Llew Roderick (Leuven) and Prof Christian Soeller (Exeter). In her thesis, Hilary investigated the calcium signals that lead to growth of heart cells in disease conditions, by developing new mathematical models of calcium dynamics within heart cells.
After completing her thesis, Hilary was awarded the Australian Mathematical Society Lift-off Fellowship.
Hilary will be joining Prof Lee Sweetlove at the University of Oxford Department of Plant Sciences, to start a postdoctoral position on modelling plant metabolism.
Many congratulations to Claire, who has now successfully completed her PhD.
Claire’s thesis ‘Understanding the Regulation of Epidermal Tissue Structure by Molecular and Cellular Processes Using Multi-Scale Models’ was supervised by Dr James Osborne and Prof. Edmund Crampin. In her thesis, Claire built a multi-cellular computational model of the epidermis — the outer-most layer of the skin — to understand how epidermal height is regulated. Her study established how balance between cell-signalling, proliferation and removal maintains the epidermal thickness in healthy tissue, and also provided insight into the effects of diseases which diminish the protective role of the tissue.
Claire is now a postdoctoral fellow at the University of Amsterdam (UvA) working with Prof Alfons Hoekstra’s Computational Science Lab, as a part of the INSIST ‘in silico stroke trials’ project.
A new preprint from Stuart Johnston, with Mat Simpson (QUT), looks at a new approximation method for birth-death-movement random walks.
Normally, random walk models are approximated via an ODE (i.e. logistic growth), which predicts the population size quite well. However, because the ODE represents the number of agents as a continuum, the agent population will never actually go extinct.
Here instead we represent the random walk via an approximate state space (which includes the extinction state) and use a PDE (over time and state space) to describe how the population transitions through the state space.
This allows us to not only predict the population size accurately, but also determine the probability that the population has gone extinct by a certain time.
Read it here:
Predicting population extinction in lattice-based birth-death-movement models
S.T. Johnston, M.J. Simpson, E.J. Crampin arXiv:2002.05357
Our latest paper, which has just appeared online in the Journal of Theoretical Biology, considers how to build simplified, yet physically plausible mathematical models of complex biological systems. Our aim is to help speed up development of whole-cell models – i.e. virtual cell models which simulate all underlying biochemical processes occurring in a cell. To achieve this it is necessary to adopt a modular approach, in which different components are modelled individually and are subsequently assembled into a model of the whole system. For this to work these model components have to ‘play nicely’ with each other. One way to ensure that model components are compatible, and will plug together into a functioning composite model, is to require them to conform to basic physical conservation principles and thermodynamic consistency.
At the same time, however, to construct whole-cell models we also need simplified representations which capture essential biophysical features while avoiding unnecessarily complexity. In our new paper, using energy generation in the mitochondrial electron transport chain as an example, we demonstrate an approach to developing simplified but thermodynamically consistent models (which we call ‘physically-plausible’ models). We show that these physically-plausible models behave like the full system and can readily be incorporated into large scale biochemical simulations, without the requirement of full mechanistic simulation of the underlying biochemical processes. We think this is a significant step towards a modular and multi-scale framework for the development of genome-scale whole-cell models.
P.J. Gawthrop, P. Cudmore, E.J. Crampin Physically-Plausible Modelling of Biomolecular Systems: A Simplified, Energy-Based Model of the Mitochondrial Electron Transport Chain
Journal of Theoretical Biology https://doi.org/10.1016/j.jtbi.2020.110223
Our congratulations to Michael Pan, who has been awarded his PhD at the Systems Biology Lab for his thesis entitled “A bond graph approach to integrative biophysical modelling”.
In his thesis, Michael used bond graph methodology to examine how energy is transferred between different biochemical and biophysical processes within cells. He developed new mathematical and computational methods for the analysis of energy flow within cellular biochemical networks and applied these methods to study heart cells. His work provides a foundation for the development of detailed modular, energy-based computational models to direct future advances in biotechnology.