Biomathematics - insulin signalling, glucose transport, microscopy image analysis, electrically excitable cells, neural networks, cardiac pacemakers, nonlinear oscillators
Field of Research (FoR)
I am an applied mathematician. I use dynamical systems analyses, stochastic modelling and queueing theory, amongst other techniques to answer questions arising from fields other than mathematics. My research is in mathematical modelling, particularly in biomedicine and biology. The investigations in which I am currently involved range from understanding the dynamics of fundamental protein-protein interactions, cellular processes,...view more
I am an applied mathematician. I use dynamical systems analyses, stochastic modelling and queueing theory, amongst other techniques to answer questions arising from fields other than mathematics. My research is in mathematical modelling, particularly in biomedicine and biology. The investigations in which I am currently involved range from understanding the dynamics of fundamental protein-protein interactions, cellular processes, the geometrical morphological features of microfossils, to the interactions in systems at larger scales involving human subjects. Projects include the modelling of
- cellular glucose transport in response to insulin and the deleterious effects insulin resistance and diabetes;
- the dynamics of electrically excitable cells such as peripheral nerves and the cardiac pacemaker; and
- starch grains within edible plants, allowing the identification of both contemporary grains and those found on ancient tools
- PhD, 1998 University of New South Wales
- BSc, First Class Honours, University Medal, 1991 University of New South Wales
As part of an ARC Discovery Project 2021-2023, there are opportunities for students and a postdoctoral researcher to work on new stochastic mathematical models of the dynamics of protein transport and cell signalling. The mathematics will link macro scale biological observations to micro scale molecular movements to characterise the relative role that different components and processes play. Expected outcomes are robust mathematical analyses of the transient dynamics of closed, finite capacity queueing networks and biological insight into the major control mechanisms in cellular insulin signalling.
To use mathematics to go where other disciplines cannot go alone. To develop novel and quantitative insight into interesting biological problems.
Research in Detail
Interdisciplinary research flourishes with the interaction of different discipline experts. Some of the projects and the collaborators with whom I'm involved are outlined below.
Insulin Signalling, Glucose Transport and Metabolic Health
My research in this area is in collaboration with experimentalists such as Cynthia Mastick of the University of Nevada, Reno, USA, David James at the University of Sydney and Dorit Samocha-Bonet at the Garvan Institute for Medical Research, Sydney. The work focuses on creation of mathematical models that robustly and quantitatively describe the movement of glucose transporters within cells, and how this is regulated and controlled by the insulin signalling network. The quantitative understanding of this dynamic system under normal conditions is essential to the future understanding of the mechanisms underlying insulin resistance and its subsequent progression to Type 2 diabetes. One of the key outcomes will be the ability to quantitatively analyse the impact of differentially regulating the activity of components of the insulin signalling network, and, in the future, be a step in the process of drug design.
An important aspect of this is the integration of the information from various sources including cellular assays, western blot and mass spectrometry techniques as well as single cell experiments using total internal reflection fluorescence (TIRF) microscopy. In order to understand complex images seen in the latter, mathematical models of vesicular events as seen by TIRF were derived as part of the development of automated image analysis and event detection software. This enables the processing of large amounts of biological information which would otherwise be untenable. It also means that the results gathered are robust.
At a higher level, I employ bioinformatic techniques to correlate and understand the large lipidomic and proteomic data sets gathered from studies into the insulin response in human plasma and muscle.
The ionic currents underlying the electrical behaviour of neurons and pacemaker cells in the heart may be described using coupled nonlinear differential equations. These have been derived in a number of different models from a wide range of electrophysiological data in the literature.
In the cardiac system the dynamics of both single cells and coupled networks of cells is being explored, and the robustness of the models to changes in parameters ascertained. Different models for the sinoatrial node cells are assessed both analytically and computationally, correlating the different responses with the ionic currents, with a view to further optimising the system.
Explorations are being made of mathematical models of the human motor axon that utilise coupled differential equations to describe the electrical activity within the nerve. These models are being used to interpret the measured responses to extended hyperpolarization and the contribution of different ion currents to the transmission of signals. The responses of sensory neurons to strong long-lasting hyperpolarization are being assessed and contrasted with motor neurons. Extensions to the models are being made to incorporate additional inhomogeneities within the neuron structure. This project is in collaboration with James Howells at the University of Sydney.
Protein-protein interactions: Modelling the interplay between tropomyosin and actin
A combination of, both continuous dynamical systems and discrete mathematical modelling and single molecule fluorescence microscopy is being used to probe the dynamic interactions of two proteins, actin and tropomyosin. With experimental partners including Till Böcking in the Faculty of Medicine the aim is to resolve how filaments of these proteins are assembled. This is important because these proteins form the cytoskeleton (the internal scaffolding) of cells. Understanding of their interactions can then be used in the future to understand how drugs can target specific components and functions of the cytoskeleton that are hijacked in cancer cells. This project focuses on the formulation of a quantitative dynamical description of the processes taking place, using experimental information to estimate meaningful and quantitative parameters to robustly test and adapt the models of the dynamical systems, enabling the differentiation between different hypotheses of mechanism and function in this interaction. Analysis of microscopy image sequences and deconstruction into a basis set for the laments are being used to estimate the rate constants of the processes. Computational work for image processing as well as analysis is being undertaken alongside dynamical systems modelling.
Identification and Classification of Starch Grains
Moving away from dynamical systems, another interesting problem that benefits from a mathematical approach arises in the identification of the food sources ground on ancient stone tools. This involves the analysis of starch grains in the residue found on the tools. I have developed mathematical methods and software based on Fourier decomposition and shape analysis to quantify the geometric morphometric features of the starch grains from microscopy images. Machine learning algorithms are then developed to classify and characterise the grains, comparing the unknown archeological samples to that from reference material from plants in the region. This work is in collaboration with Judith Field of the School of Biology, Earth and Environmental Sciences.
Recent Research Grants
- ARC Discovery Project 2021-2023, The mathematics of stochastic transport and signalling in cells
- ARC Discovery Project 2018-2020, Dynamical systems theory and mathematical modelling of viral infections, with Peter Kim, Federico Frascoli and Chae-Ok Yun.
- ARC Discovery Project 2013-2015, Resolving the mechanisms of actin filament specialisation through single molecule analysis and modelling, with Till Böcking.
Student Projects (PhD and Honours)
Topics include, but are not limited to those above, i.e.
- Mathematical modelling of the insulin signalling pathway and glucose transport,
- The dynamics and stability of cardiac pacemaker cells, and
- Modelling the interaction of actin and tropomyosin.
Please email me if you are interested in these or other biomathematical projects. Please include some information about your mathematical background and interests.
Advice for prospective students
Maths and science are the building blocks for understanding the world around you. Enjoy, be passionate and above all have fun with your studies. You will find that this will intensify as you discover your specific specialty. Interdisciplinary research is particularly exciting as it integrates the techniques and knowledge of, for instance, biology and mathematics, to create much deeper understanding of the problems than either discipline alone.
TEACHING & OUTREACH
Courses I teach
I am currently involved in subjects such as
MATH1131 Mathematics 1A
MATH3041 Mathematical Modelling for Real World Systems
MATH3201 Dynamical Systems and Chaos
MATH3121 Mathematical Methods and Partial Differential Equations
Professional affiliations and service positions
Past-President of the Australian Society for Biophysics.
I chair the Academic Committee in the School of Mathematics & Statistics.
I am a former member of the UNSW Academic Board and serve on many School, Faculty and University committees.