Research interests

I’m broadly interested in the application of computation and mathematics to medicine, but at the moment I enjoy looking at the genetics of transcript splicing and the how these relate to the interactions between humans and microbes, and what this can tell us about how GWAS loci modulate risk.

Current topics

At the moment I’m in my final year of the 4-year Wellcome Trust PhD Programme in Mathematical Genomics and Medicine. Having previously done a rotation project in Emma Davenport’s lab at the Sanger Institute, I then decided to make this my full PhD Project. I’m focusing on human variation in gene transcription (such as alternative splicing) and how this contributes to the heterogeneity of immune responses. I’ll also be looking at the interactions of different microbes (both pathogenic and commensal) on this.

Previous projects

Phylogenomic analysis of an infant gut commensal

For my second rotation project, I performed the largest to-date analysis of the infant probiotic bacteria Bifidobacterium breve. This was in the lab of Trevor Lawley at the Wellcome Sanger Institute. By looking at a collection of 414 genomes, I was able to contrast the metabolic potential of each, as well as make inferences about the distribution and capabilities of the species. I also demonstrated that existing studies which have only assessed in the order of 20-30 isolates are vastly under powered and neglect geographically diverse lineages which I correct for.

Asthma transcription network analyses

In the lab of Mike Inouye at the Baker Heart and Diabetes Institute in Melbourne, Australia, I clustered gene expression networks to aid in analysing the development and progression of asthma in infants. This approach summarises large groups of similarly-regulated genes as clusters to simplify downstream analysis.

Plasmid genomics

With Kat Holt at the Bio21 Institute in Melbourne, Australia, I analysed the genetics of plasmids in bacteria using a network based approach. This was based on the observation that even among closely related plasmids, their shared genetic content wildly differs, and can easily become mixed up with the genes of the host bacteria. Scripts for running and visualising this yourself is available on GitHub.

Cardiac transcriptomics

In the lab of Mirana Ramialison at the Australian Regenerative Medicine Institute in Clayton, Australia, I explored how heart transcription data could be interactively visualised in 3D. This visualisation can be run in a web browser, and is accessible online at 3D Cardiomics. We also have a paper out in the Journal of Molecular and Cellular Cardiology.