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Computational Biology

The Computational Biology Group engages in theoretical and applied, interdisciplinary and practise-based research at the interface between computer science, mathematics and the biomedical sciences. Our research focuses 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 Systeme Biology DTCs, the BBSRC/EPSRC-funded Centre for Integrative Systems Biology, and the EU FP7 projects euHeart and PreDiCT.

 

D.Phil Funding available

The Doctoral Training Centre has around 40 D.Phil studentships available annually across a range of interdisciplinary areas including Computational Biology (this includes a small number available to international students). Please follow this link for details.

Related seminar series

All Activities

Activities

Computational Biology group The Computational Biology Group, led by Professor David Gavaghan, is …

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Computational Heart Modelling The Computational Heart Modelling and Simulation Group at Oxford incl…

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All Projects

Projects

2020 Science 2020 Science is focused on fostering the creation of a new generation…

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Translating Biochemical Modelling into the Heart of the Clinic

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All Publications

Publications

The Cardiac Electrophysiology Web Lab

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Hydroxychloroquine reduces heart rate by modulating the hyperpolarisation activated current ‘If’: Novel electrophysiological insights and therapeutic potential

Read more about Hydroxychloroquine reduces heart rate by modulating the hyperpolarisation activated current ‘If’: Novel electrophysiological insights and therapeutic potential

Research