Samira Asgari describes how her research programme focuses on overlooked populations in human genomics.
Nikki Forrester 11 February 2021
Joining a newly established laboratory as its first PhD student gave Samira Asgari a great foretaste of life as an independent researcher and insights into setting up a research programme from scratch.
Computational biologist Samira Asgari’s work focuses on communities and individuals who are often overlooked in studies on human genetics, especially Peruvian and Afro-Caribbean populations. Last year, she received a Nature Research Award for Inspiring and Innovating Science, which is awarded in partnership with The Estée Lauder Companies.
What is your background in science?
I did my bachelor’s and master’s degrees at the University of Tehran, where I studied biotechnology. After finishing there, I had offers to join two labs focused on genetics at the Swiss Federal Institute of Technology in Lausanne (EPFL) for my PhD — one led by a new professor, Jacques Fellay, and the other by a well-established professor, Didier Trono. Trono told me, “If you join my lab, it’ll be like cooking. If you join Fellay’s lab, it’ll be like writing a cookbook.” That helped me a lot: I don’t like cooking. In 2012, I joined Fellay’s lab as his first PhD student. It was a bit of a risk because he had started working at EPFL only a few months before I arrived. Instead of following established protocols in a big lab, we had to develop everything on our own: I had to write the cookbook.
My PhD research in computational biology focused on understanding why some children get sick from common respiratory viruses, such as the respiratory syncytial virus. My hypothesis was that these children have some genetic background that makes them particularly sensitive. I knew almost nothing about programming or data analysis when I started. To learn, I spent a lot of my first year reading Internet forums, such as Biostar and Stack Overflow, and I took a programming course at the university. I also asked colleagues who worked in more-experimental labs about DNA-extraction protocols and other genetics techniques.
That cooking analogy set the tone and direction for my whole career as a computational biologist. By seeking out resources and learning skills on my own during my PhD programme, I learnt how to be independent, how to lead a research programme and where to find help when I need it. I still do ‘cookbook writing’ science, and plan to continue. For instance, the analyses I conduct on genetics data can serve as ‘recipes’ for experimental biologists to expand on.