Research

Our research falls broadly into three areas:

Within each of these broad areas we are pursuing several different projects, and developing common mathematical approaches and computational tools.

Earlier work in the group focused on Modelling Lung Epithelial Cells, Network Inference in Cancer and Biological Pattern Formation.


The Virtual Heart Cell Project

Cellular function is determined by the complex network of interacting biological processes occurring within and between cells. Integrative modelling provides a means of assessing the quantitative contribution of each of these components, and assessing potential therapeutic strategies in disease. With a focus on understanding regulatory mechanisms, we are developing biophysically-based models of a range of cellular processes in relation to heart cell function and heart disease.

It is well established that cellular structure affects its function and that cellular function can in turn trigger structural remodeling. But can we predict the effect of a structural alteration on cellular function? Do we know the mechanism by which cellular function drives structural remodeling? Working with Vijay Rajagopal’s Cellular Structure and Mechanobiology Group, we are addressing these questions by developing a computational modeling framework for simulating cellular systems biology within the 3D spatial structure of the heart cell and its local environment. This framework integrates structural imaging data and quantitative functional data to create realistic simulations of structure-driven function and function-driven structural remodeling.

Recent Publications:

IP3R Ca2+ release shapes the cytosolic Ca2+ transient for hypertrophic signalling in cardiomyocytes
H. Hunt, A. Tilūnaitė, G. Bass, C. Soeller, L. Roderick, V. Rajagopal, E.J. Crampin (2020)
Biophysical Journal 119 (6), 1178-1192

Assessing cardiomyocyte excitation-contraction coupling site detection from live cell imaging using a structurally-realistic computational model of calcium release
D. Ladd, A. Tilunaite, H.L. Roderick, C. Soeller, E.J. Crampin, V. Rajagopal (2019)
Frontiers in Physiology 10:1263

Bond graph modelling of the cardiac action potential: implications for drift and non-unique steady states
M. Pan, P.J. Gawthrop, K. Tran, J. Cursons, E.J. Crampin (2018)
Proceedings of the Royal Society A 474: 20180106

Insights on the impact of mitochondrial organisation on bioenergetics in high-resolution computational models of cardiac cell architecture
S. Ghosh. K. Tran, L. Delbridge, A. Hickey, E. Hanssen, E.J. Crampin, V. Rajagopal (2018)
PLoS Computational Biology 14(12): e1006640


Energy-Based Modelling for Systems and Synthetic Biology

Energy is fundamental to all life. In systems biology, models typically consider biochemical reaction rates, and hence fluxes of different biochemical species. However energy is almost universally ignored. In our view this significantly restricts the types of questions that models can be used to address, and limits the applicability of systems biology models in design for synthetic biology and biotechnological applications. We are developing energy-based models of biological systems based on multi-domain engineering concepts, which use the bond graph approach to represent both mass and energy flows.

Recent Publications:

Physically-Plausible Modelling of Biomolecular Systems: A Simplified, Energy-Based Model of the Mitochondrial Electron Transport Chain
P.J. Gawthrop, P. Cudmore, E.J. Crampin (2020)
Journal of Theoretical Biology, 493, 110223

A thermodynamic framework for modelling membrane transporters
M. Pan, P.J. Gawthrop, J. Cursons, K. Tran, E.J. Crampin (2019)
Journal of Theoretical Biology 481, 10-23

Energy-based Analysis of Biomolecular Pathways
P.J. Gawthrop, E.J. Crampin (2017)
Proceedings of the Royal Society A 473:20160825

Modular Bond Graph Modelling and Analysis of Biomolecular Systems
P.J. Gawthrop, E.J. Crampin (2016)
IET Systems Biology 10 (5) 187-201


Modelling Bio-Nano Interactions for Nanomedicine

F1.largeUnderstanding how nano-scale materials and cells interact will be key to the future development of improved nanomedicines and vaccines. At the ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, we are leading the ‘Modelling of Bio-Nano Interactions’ theme, where our aim is to understand the rules by which cells interact with nanoengineered particle systems with tailored physical properties. The long term aim is to develop models with which we can design nanoparticles with predictable cellular interactions.

Recent Publications:

Understanding nano-engineered particle-cell interactions: biological insights from mathematical models
S.T Johnston, M. Faria, E.J. Crampin (2021)
Nanoscale Advances, 2021, DOI: 10.1039/D0NA00774A 

Revisiting cell–particle association in vitro: A quantitative method to compare particle performance
M. Faria, K.F. Noi, Q. Dai, M. Björnmalm, S.T. Johnston, K. Kempe, F. Caruso, E.J. Crampin (2019) Journal of Controlled Release 307, 355-367

Link between Low-Fouling and Stealth ‒ A Whole Blood Biomolecular Corona and Cellular Association Analysis on Nanoengineered Particles
A.C.G. Weiss, H.G. Kelly, M. Faria, Q.A. Besford, A.K. Wheatley, C.-S. Ang, E.J. Crampin, F. Caruso, S.J. Kent (2019)
ACS Nano 13 (5), 4980–4991

Minimum Information Reporting in Bio–Nano Experimental Literature
M. Faria, M. Björnmalm, K.J. Thurecht, S.J. Kent, R.G. Parton, M. Kavallaris, A.P.R. Johnston, J.J. Gooding, S.R. Corrie, B.J. Boyd, P. Thordarson, A.K. Whittaker, M.M. Stevens, C.A. Prestidge, C.J.H. Porter, W.J. Parak, T.P. Davis, E.J. Crampin*, F. Caruso* (2018)
Nature Nanotechnology 13, 777–785