Research Areas
Analytical Experiments
- Projects involve the development of tailor-made software tools for the analysis and interpretation of data, such as transcriptional profiles and time series imaging data. Modelling includes tools for deducing network parameters, structure and dynamics, and parameter reduction.
- Experimental approaches include, microarray techniques and biological imaging
- Mathematical approaches include novel Bayesian hierachical clustering methods, Gaussian and heavy-tail noise models, linear and non-linear models, hidden variable and augmentation models
Cellular Mechanics/Spatial Systems biology
- Projects include Natural Killer Cell Signalling, Actin Dynamics, and Single Cell Tracking in High Throughput Experiments
- Experimental approaches include confocal imaging, single cell protein dynamics
- Mathematical approaches include quantitiative image analysis, mechanistic modelling, and statistical methods to analyse spatio-temporal dynamics
Medical Systems Biology
- Projects include Reproductive Medicine, Energy Balance Regulation, Vascular Health and Ageing, Thiamine Metabolism and Diabetes, Preganglionic Motor Neurones, and Nitric Oxide Biology
- Experimental approaches include electrophysiology, confocal microscopy, fluorescence imaging
- Mathematical approaches include modelling of neuroendocrine control, and pharmokinetic modelling
Microbiology
- Projects include Global Metabolic switching in Streptomyces coelicolor
- Experimental approaches include microarray analysis
- Mathematical approaches include cluster analysis, and network inference
Cell Signalling
- Projects include the Dynamics and Function of the NF-κB Signalling System, and Eukaryotic G Protein Signalling
- Biological approaches include cell imaging, proteomics, chromatin immunoprecipitation, RT-PCR and microarray analysis
- Mathematical approaches stochastic and deterministic modelling, and the developments of data analysis tools
Plant Systems Biology
- Projects include Responses to Environmental Stress, Regulation of Gene Expression by the Circadian Clock, Regulation of Signalling by Temperature, and Agronomics
- Experimental approaches include functional genomics, identification of transcription factor binding sites, and proteomics
- Mathematical approaches include Bayesian state space modelling, transcription modelling, and experimental prediction
Computational Neuroscience
- Projects include studies of memory formation, hormone homeostasis, Parkinson's disease and ageing
- Experimental approaches include electrophysiology and imaging
- Mathematical approaches include stochastic modellling, modelling of reduced neurones and network dynamics
Machine Learning and Data Science
- Developing new machine learning/data science methods and tools
- Applying these tools to important problems in medicine and biology
- Competing in data science competitions (as 'Warwick Data Science')