Computational Biology Group
The Computational Biology Group, led by Professor David Gavaghan, is an interdisciplinary group based within the Department of Computer Science. The group engages in theoretical and applied, interdisciplinary and practise-based research at the interface between computer science and the biomedical sciences, focussing on applying computer science and mathematical techniques to clinically and biologically pressing problems. Key applications include physiological modelling (heart, cardiovascular and cardiorespiratory systems, soft tissue mechanics and cancer), biological image and signal analysis, and systems biology. Work is almost entirely done jointly with domain specialists in life sciences and clinical departments. The Computational Biology Group also plays a key role in interdisciplinary initiatives across the University, including the Life Sciences Interface and Systems Biology DTCs which are led by Professor Gavaghan and the BBSRC/EPSRC-funded Centre for Integrative Systems Biology.
Control of NFAT Isoform Activation and NFAT−Dependent Gene Expression through Two Coincident and Spatially Segregated Intracellular Ca2+ Signals
P Kar‚ GR Mirams‚ HC Christian and AB Parekh
In Molecular Cell. Vol. 64. No. 4. Pages 746−759. 2016.
Hierarchical Bayesian inference for ion channel screening dose−response data [version 1; referees: awaiting peer review]
RH Johnstone‚ R Bardenet‚ DJ Gavaghan and GR Mirams
In Wellcome Open Research. Vol. 1. Pages 6. 2016.
White Paper: Uncertainty and variability in computational and mathematical models of cardiac physiology
GR Mirams‚ P Pathmanathan‚ RA Gray‚ P Challenor and RH Clayton
In Journal of Physiology. 2016.