Computational modelling of calcium signalling in heart growth
Project Leader: Vijayaraghavan Rajagopal
Student: Nathan Isles
Collaborators: Edmund Crampin (BME, Math and Stats), Eric Hanssen (Bio21 Institute) David Collins (BME), Llewelyn Roderick (KU Leuven), Christian Soeller (University of Exeter) Julie McMullen (Baker Institute)
Sponsors: Australian Research Council
Primary Contact: Vijay Rajagopal, Edmund Crampin (email@example.com)
Keywords: cardiovascular disease; cell development; heart; numerical modelling; systems biology
Disciplines: Biomedical Engineering,Chemical & Biomolecular Engineering,Computing and Information Systems
Domains: Convergence of engineering and IT with the life sciences
Research Centre: Systems Biology Laboratory
Our hearts beat roughly 2.2 billion times through the course of our lives. Unlike man-made pumps that have a fixed operating range for pumping fluid, the heart has an amazing capacity to simultaneously modulate the force and rate with which it contracts to meet changes in our body’s demand for blood supply. Short term changes in blood supply demand (eg, sprinting or climbing stairs) are met by increasing the heartrate. Long-term changes (over weeks and months) occur with endurance training, pregnancy and growth into adulthood. An increased heartrate cannot sustain these long-term changes. Instead, the heart adapts to long-term changes by increasing its size through a process called hypertrophy. The heart’s size is governed by the size of each of its constituent cardiac cells and not by the number of cells; cardiac cell growth is governed by the cell nucleus.
The goal of this project is to address a fundamental gap in our understanding of what signal in the cell nucleus triggers hypertrophic cell growth. This missing knowledge has implications across cell biology because of the fundamental importance of hypertrophy to biological systems. A fundamental understanding of how hypertrophy is triggered in the cell nucleus has implications for treating many heart related diseases, including high blood pressure or diabetes, where hypertrophy is triggered as an adaptation but often exacerbates the condition and leads to death.
We are seeking outstanding graduates with a Bachelors or Masters degree in Applied Mathematics, or Engineering, with a strong background in one or several of the following techniques to join our team:
- Nonlinear dynamical systems modelling
- Stochastic process modelling
- Finite element modelling
- Computational systems biology including biological network modelling, mass action kinetics modelling.
Further information: https://biomedical.eng.unimelb.edu.au/cell-structure-mechanobiology/ https://www.sciencedirect.com/science/article/pii/S0006349520305968 https://www.frontiersin.org/articles/10.3389/fphys.2019.01263/full