GA4GH Community Spotlight: Mélanie Courtot

5 Nov 2021

This GA4GH Community Post is the sixth in our monthly series featuring individuals from across GA4GH. This month we are turning the spotlight on Mélanie Courtot!

This GA4GH Community Post is the sixth in our monthly series featuring individuals from across GA4GH. This month we are turning the spotlight on Mélanie Courtot! Mélanie is the metadata standards coordinator for the archival and infrastructure team at the European Bioinformatics Institute (EMBL-EBI) in Cambridge, UK. Her background is in structural biochemistry, computer science, and bioinformatics, with a focus on knowledge representation and semantic engineering. At EMBL-EBI, she designs tools to streamline multi-omics submissions and develops integrated metadata strategies across the institute’s archival resources and other projects such as FAIRPlus, focusing on data quality, semantic enrichment, and standardization for pharmaceutical and cohort data respectively. Dr. Courtot is passionate about translational informatics – building intelligent systems to gain new insights and impact human health. She co-leads the Data Use and Cohort Representation subgroups for the Global Alliance for Genomics and Health (GA4GH), as well as cohort harmonization efforts for Common Infrastructure for National Cohorts in Europe, Canada, and Africa (CINECA), the International HundredK+ Cohorts Consortium (IHCC), and the Davos Alzheimer’s Collaborative.

Why are interoperability and data sharing important to your work and career?
While we know how to generate a lot of data, without the means to integrate it across systems, understand and analyse it to derive new insights, we are effectively lost on a road in the middle of a desert with no map. Interoperable data allows me to build a network of paths, and data sharing means I can extend that network across a growing knowledge map. The intelligent systems I build can answer research questions of importance to human health, biology, and society.

What scientific discovery throughout history is most fascinating to you?
That is a hard question! If I had to pick only one, I would choose John Snow’s investigation of a Cholera outbreak in London in 1854. He collected data from local residents and identified a specific water pump as the source for the spread of the (at the time unknown) virus, and removing the manual pump handle has been credited with helping stop the outbreak. This story is fascinating as John Snow went against the state-of-the-art knowledge at the time (miasma rather than germ theory of disease), driven purely by his observation and the data. He collected and integrated information from residents, mapped the spread of disease, and based on his analysis, proposed an effective public health solution. This is not dissimilar to what GA4GH aims to do: bring data together to benefit and advance human health and why I am personally so inspired by the GA4GH vision.

What advice would you give to individuals seeking to get more involved with GA4GH?
I love the diversity of the GA4GH community. GA4GH brings together a wide range of profiles from junior to senior, across many countries, at different stages in their careers, and in many disciplines; we simply won’t develop global solutions without being global. It is truly inspiring and motivating to work with such a wealth of experience and expertise. When first joining, the sheer number of people and projects can be daunting, and I’m really happy to see the new efforts to ease onboarding being spearheaded by our Equity, Diversity, and Inclusion Advisory group. My advice to interested parties would be to take the plunge, and immerse themselves in some of the Work Streams. Do ask questions and contribute to discussions: new opinions and input are highly valued, and we’re a welcoming bunch.

How do you think genomic data standards will shape the world in 20 years?
I dream of a world where my children can get tailored, bespoke prevention for disease. I would love for their genomic data to be analysed and interpreted for treatment – we do some of this right now with breast cancer for example, but I’d love to see this broadly expanded. We still have a long way to go in understanding how the environment plays a role in health, and being able to integrate social, physical, and biological data to elucidate its effects on phenotypes. Providing the right info at the right time to the right individual will be critical in alleviating the burden of disease. As the technologies to generate data have made so much progress, I truly believe we are on the cusp of amazing discoveries, and I am proud to contribute to projects that will shape the future of mankind.

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