Bobbie is our resident genomics wizard, who knows a thing or two about data pipelines and draws inspiration from the film Mad Max and his two dear whippet babies. Meet our much loved social ‘glue’ of MDAP, Bobbie!
Hi Bobbie! Can you please tell us a bit about your career trajectory so far?
I have a double degree in Computer Science and Molecular Biology which I received from Murdoch University back in 2003. I then went to the UK to work for the Health Protection Agency, now Public Health England where I developed the Enteric Molecular Typing Network (EMTy-NET) which captured data related to food borne pathogen outbreaks. I also worked on the First Few 100 website which captured enhanced data collections from the first first contractors of the 2009 UK H1N1 influenza pandemic.
My next move was to move from my hometown, Perth, to Melbourne to work for the Australian Genome Research Facility (AGRF) where I further developed my Bioinformatic skills in RNASeq, Genomic Assembly and Virus discovery workflows. My area of specialty is discovering novel RNA viral sequences from metaviral samples using a suite of bioinformatic tools and have used this workflow in a number of publications.
After 5 years at AGRF I moved to the University of Melbourne where I worked as a Genomics Data Specialist at Melbourne Integrative Genomics (MIG), where I developed computational workflows on HPC systems applying optimisation techniques to improve speed and efficiency of processing Big Data. My years at MIG allowed me to develop my interests in high performance computational workflows for which is a big part of my work at MDAP.
Tell us about an interesting project at MDAP?
In the last round of collaborations we were processing 50 terabytes of metagenomic data for A/Prof Heroen Verbruggen in a project named “Unlocking published metagenomes as a source of information for microbial eukaryotes”. This project allowed us (my brilliant MDAP colleagues and myself) to further develop and refine MetaGenePipe, a metagenomics workflow I initially began to develop at MIG, to allow optimised processing, storage and interrogating of large, publicly available datasets and provide researchers with functional gene annotations and counts to be used further downstream in advanced metagenomics analyses.
MetaGenePipe has been created with WDL for use on high performance and standalone systems with integration into cloud based technologies to follow. MetaGenePipe is robust and flexible enough to be used on Prokaryotic or Eukaryotic data and optimised to process 50Tb of data quickly depending on the scalability of resources available.
What are some of the solvable, difficult, and wicked problems on your horizon?
My aim is to take long-standing bioinformatics techniques and paradigms and apply them to different domains. My current collaborations, The Heart: Gathering real-time building data for an art installation with Dr Robert Walton, A Fair Day’s Work: Detecting wage theft with Professor John Howe and Tackling the canine microbiome in chronic enteropathy with Professor Caroline Mansfield will allow me, I believe, to take general bioinformatics principles, algorithms and paradigms and apply them to seemingly contrasting fields.
Can you tell us about your latest adventure or next planned one outside of MDAP?
With covid still a daily reality it’s difficult to plan long term for lack of certainty with moving around Australia and the Globe so most of my current planned activities are home-bound and include home brewing beer (my favourite is red ale!), antique hunting (restrictions permitting), watching historical television shows, playing cricket, cooking and sharing photos with my colleagues and taking my two whippets, Ada Lovelace and Professor Archibald Krumbsnatcher (The plotter of misdeeds) on walks.
In the context of a rapidly evolving global environment and UoM’s research strategy, what would you most like to explore, challenge, or innovate in your work in the future?
I see that there is a growing need for interdisciplinary research methods and I would like to use established bioinformatics paradigms in other research areas. By defining DNA as a form of text the same DNA search algorithms (such as the Smith-Waterman) can be taken and adapted to volumes of text to speedily identify patterns and interesting features which may be hidden from traditional algorithms due to colloquialisms in writing. My partner who is currently undertaking her PhD in History could have used such an algorithm not only to discover references but to discover the absence of references in large volumes of text quickly and efficiently.
I have found that when people merge their “disparate” interests, the environment it creates supports discovery and advances. I would like to merge my interest in History, Viruses and Ancient DNA to see if there are any useful insights from historical DNA which can produce advances and tools in infection disease research.