Early Career Research Fellow in Biodiversity Informatics & Spatial Analysis, Royal Botanic Gardens, Kew
Phylogenomics, high-throughput real-time bioinformatics, evolutionary biology, macroevolution and bioinformatics, viral evolution, in silico virological research and vaccine development, and epidemiological modelling. Also, reproducible research, open data and sustainable software development, cloud computing, scalable architectures for bioinformatics research and development, accessible computing for independent researchers and research in developing nations.
I want to examine and analyse living organisms’ DNA sequences in the field - as simply, quickly, and cheaply as we measure their height, weight or any other aspect of their physical appearance.
Over time, organisms’ DNA sequences evolve in response to their changing environments, competitors and predators. By comparing similar gene sequences between species and individuals, we can use the numbers and patterns of these changes to infer their evolutionary history – for instance, when did two species diverge? Which genes were the most important for their survival? How many individuals where there in each population, and how have they spread across the globe?
These ‘phylogenetic’ studies have now shifted into a whole new gear as both computing power and sequencing ability (the speed and cost to read letters of DNA from a genome) have expanded by several orders of magnitude. We’re discovering that, although the basic principles of molecular evolution hold true, the variety and detail by which these patterns are realised in DNA sequences reflect the infinite multiplicity of physical forms seen in the natural world.
In particular, it turns out that – against all expectations – DNA sequences in unrelated organisms (for example bats and dolphins) can, in certain circumstances, become more similar over time, not less. My research exploits the power of massively parallel DNA sequencing and computing clusters to build a statistical picture of DNA evolution across whole genomes, and we are finding exceptions to the every rule in the book.