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Research at the interface of evolution, informatics, and ecology
Phylogenomics, Evolution and Bioinformatics by Lonely Joe Parker
Biology is changing. In the space of a decade the mechanics of reading living things' DNA codes has moved from a specialised job taking weeks and hundreds of thousands of pounds, to a simple procedure many people could carry out in their own home. The implications for evolutionary biology, genetics, medicine, agriculture and conservation are profound. The challenge is to analyse this torrent of data. I build bioinformatics apps to automatically process DNA data immediately, as it is generated: 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.
I am a Research Fellow in Phylogenomics at the National Biofilms Innovation Centre and a Fellow of the Software Sustainability Institute.
The coming ubiquity of both portable DNA sequencers and cloud computation mean scenarios formerly found in sci-fi films (instant DNA analysis) are coming, soon. I'm developing methods to streamline DNA sequence analysis using cloud computation.
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Up to 80% of the microscopic organisms on the Earth exist not as solitary cells, but 'biofilms'. These are complex, three-dimensional slimy structures where bacteria (and other microorganisms) co-exist, resisting our attempts to remove or kill them with antibiotics.
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Modern DNA sequencers are highly portable, compared to lab-bound models of a decade ago. I'm trialling field-based sequencing using the MinION USB sequencer - a palm-size device with potential to revolutionise environmental metagenomics and turbotaxonomy.
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Phylogenomic big-data allows us to detect statistical patterns with weak effects, such as adaptive convergent molecular evolution. I'm also interested in patterns of gene family evolution, homology, and divergent adaptive selection.
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Phylogenomic models accounting for uncertainty require useful metrics on tree space - the 'distance' between two or more phylogenetic trees. However few useful such measures exist and I'm hunting for more...
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The vast scale of bioinformatics datasets currently being assembled require models of asynchronous computation; meta-algorithms where model areas are updated asynchronously on separate machines.
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Development of sustainable software and open research norms is a priority for big-data empirical bioscience in the 21st centrury, to avoid the 'reproducibility crisis'. I'm a Fellow of the SSI.
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I'm interested in the parallels and divergences between the natural world (in a systems biology context) and organisation of human societies. Maybe I'll get to take a sabbatical one day!
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