Meet Noel, our in-house bioinformatics and genetics specialist with a knack for tackling complex computational challenges in health and biological sciences and enjoying backyard travel in lieu of European getaways for now.
Noel! Please tell us a bit about your career trajectory so far.
I undertook a Bachelor of Science (Biochemistry and Genetics) with Honours (Genetics) at La Trobe University. I then worked for four years as a wet lab bench research assistant in a small Biotech company (InGenKo) based at Monash Institute for Reproduction, designing and building the genetic constructs for gene knock-out and knock-in mice. During this time, the human genome was being published and the use of computational techniques for genomic data was starting to ramp up. So I decided to move out of the wet lab and into the dry.
I then embarked on a Graduate Diploma in Computer Science and followed up with a PhD in Bioinformatics, at Monash University, to understand the functional and evolutional role singe amino acid repeats have in proteins. I then worked as a researcher at the National ICT Australia Victoria Lab, where I applied machine learning in oncology and then moved into the dementia research field, at the Florey Institute for Neuroscience and Mental Health, applying machine learning to discover blood-based biomarkers for Alzheimer’s disease as well as biostatistics to uncover the important impact of elevated brain iron on the progression of cognitive decline in Alzheimer’s disease.
During this time I also worked at the CRC for Mental Health, where the issues of research data management come to the fore, and I worked on developing a clinical system to capture and manage Parkinson’s disease (PD) clinical data, as well as advocating for improved research data management to enable reproducible research. After spending around eight years in a large national consortium and being very productive, I moved into industrial research, IBM Research Australia, where for four years I worked in the biomedical space on natural language processing (NLP) problems, and researched biomarkers for Alzheimer’s disease and models of prognosis, from blood, genomics and retinal images. After four and a half years I made the move back to academia, and started with MDAP in 2020.
Note: I am yet to leave Victoria to pursue a science career!
Can you tell us about an interesting or challenging problem at MDAP?
I am coming to an end of a collaboration with the team in the Parasitology Department in the Faculty of Veterinary and Agricultural Sciences, led by Prof Robin Gasser and Dr Neil Young who are studying the population structures of parasitic nematodes using whole-genome analysis.
We were able to increase their existing genomics workflow speed on The University’s high performance computing system, Spartan by approximately 50%.
We achieved this by unpacking the existing workflow and understanding how the pieces fit together and why certain designs where made. Slack and GitLab were so helpful to facilitate our group communications.
What are some of the solvable, difficult, or wicked problems on your horizon?
I am really excited to be starting two new collaborations, across the University. One with Prof Gustavo Duque, using Deep Learning and statistics to model falls risk in dementia patients. The other with Prof Karin Verspoor and A/Prof Douglas Boyle to evaluate the state of the art natural language processing algorithms to de-identify clinical documents in the Australia context.
Tell us about your latest planned adventure outside of MDAP.
We had planned to head back to Greece, my wife’s family is from there, so my two kids can see some of their heritage. However, given the current COVID-19 pandemic, this is on hold. So in the meantime, off to see my sister’s new place in Wandiligong and rediscover the beautiful Victorian alpine region. We have such amazing places locally, we have plenty of local adventures planned.
What would you most like to explore, challenge, or innovate in your work in the future?
Given the funding and job challenges in the sector, new and innovative career paths need to be developed. As a way to contribute to the current conversation, I would like to help build a community of “Third Spacers”, particularly across the biomedical domain, to help expose the latest compute infrastructure (locally and nationally), as well as the analytical techniques and research data management practices.
With this, we can enable smarter research practices and foster greater reproducible and replicable research.
Lead image: NHMRC