Modelling, Visualisation and Classification of Bio-Imaging

Biological imaging is undergoing rapid growth and development in microscope technology. High throughput screens for drug and genomic discovery are leading to massive image sets in need of new methods of quantification, modelling, analysis, classification, feature extraction, organisation, visualisation, comparison, hypothesis testing and inference. The core of the groups research is to develop the methodologies, algorithms and tools to maximise the benefit of the new data sources becoming available. The group collaborates closely with cell biology, developmental biology, bioinformatics and mathematics groups in creating these methodologies and utilises and develops techniques in areas such as machine learning, data clustering, graph algorithms, image segmentation, statistical testing and mathematical modelling.

Traineeships, honours and PhD projects include

• Machine learning approaches to bio-imaging
• Information visualisation and clustering methodologies
• Segmentation and quantification of microscopy imaging
• Mathematical modelling from microscopy imaging