Biomedical Data Analytics
Overview of theme
Our Biomedical Data Analytics theme spans a wide range of research topics in computational modelling for neuroscience, systems and synthetic biology, medical image processing, and developing the next-generation of AI based technologies for the analysis of pathology image data.
Our key research areas include:
Computational Neuroscience
Computational modelling for neuroscience, with a wide range of interests including molecular (LTP, LTD, hormone), neuron (abstract and biophysic), neuronal networks and behavioural (motor control).
Computational Pathology
Developing the next-generation of AI based technologies for the analysis of pathology image data, with applications to computer-assisted diagnosis and grading of cancer and image-based markers for prediction of disease outcome and survival.
Systems and Synthetic Biology
Interdisciplinary research to understand and control regulatory mechanisms of biological systems using quantitative models, high‑throughput data analysis, and applied AI. Applying engineering principles to design and construct new biological parts, or to reprogram existing biological metabolic pathways and organisms. Strong focus on impactful applications in medicine and industry.
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Publications and Projects
Our Publications list provides details of our published papers in books, journals and conferences.
We are involved in many diverse research projects funded by several external bodies such as EPSRC, National Institute for Health Research (DoH) etc.