Works across a wide range of genomics and sequence-based research both theoretical (e.g. protein function evolution) and for applied software development (e.g. antimicrobial resistance prediction). Currently focussed on the application of genomics analysis software in the public health context.
After completing a PhD in protein sequence domain analysis as part of the Pfam group at the Sanger Institute (2005), I continued in the structural world in the CATH-Gene3D group at UCL. Here I gained experience in a range of modern computational biology practices: from the large-scale via development of ontologies and web-based tools for linking primary databases through to the detailed analysis of individual proteins.
I then joined David Aanensen at Imperial College as part of the nascent CGPS team – and then onto the BDI at Oxford University – to apply this experience to building genomics analysis tools for public health researchers and decision makers. In particular I feel the rapidly growing volumes of genome-phenotype data for antimicrobial resistance is leading to a transformation in the possibilities for modelling and prediction.
Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool.
O'Toole Á. et al, (2021), Virus evolution, 7
Visualizing variation within Global Pneumococcal Sequence Clusters (GPSCs) and country population snapshots to contextualize pneumococcal isolates
Gladstone RA. et al, (2020), Microbial Genomics, 6