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Research area(s)

Bioinformatics, Computational Systems Biology, Computational Synthetic Biology; multiscale modeling, model checking, computational methods for design of biological systems.  Personalised Health Care / Systems Medicine; Systems Toxicology.  Disease epidemics and pandemics.  Computational Linguistics.

Co-leader of the Computational Biology Group, and member of the Centre for Intelligent Data Analysis

Project details

David’s initial research was in concurrent systems, computational logic, constraints and agents.  He migrated from his initial research interests to focus over the last 20 years on Bioinformatics, Systems Biology and Synthetic Biology.  His initial work in Bioinformatics was in structural biology with a focus on modelling and analysing protein structures at the fold level.  This led to fast and effective methods for protein structure comparison, motif discovery and structural alignment, exploiting computation over specialised graph-based representations of structures. He subsequently worked on developing methods for modelling and analysing biochemical pathways, both metabolic and signalling, with applications to disease including cancer, tropic parasites (Trypansoma and Plasmodium) and has recently neurological degenerative diseases.  His approach has always been to integrate computation with bioscience and engineering, and this has been exemplified by his work on Synthetic Biology  -- he co-led a highly successful team in the 2007 international Genetically Engineering Machines competition, gaining top place in the Biosensing and Environment category. David’s current research is in the area of Computational Biology, Systems Biology and Synthetic Biology.  His focus is on developing methods for modelling and analysing biochemical pathways, with particular interests in multiscale and whole system modelling and model checking.  He is also developing computational techniques to support the design and engineering of synthetic biological systems.