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Judith Blake, a geneticist working at The Jackson Laboratory, US, is March’s featured Faculty Member of the Month. For International Women’s Day, we interviewed Blake to hear more about spotting patterns in research and her career trajectory in evolutionary biology.

With a keen interest to understand how biological systems evolved, what life forms have in common and what makes them distinct, Blake has worked primarily with vertebrate systems, but also many eukaryotic organisms in her comparative genomics work. As her work has developed, her focus has changed to the organization and classification of biological data types, contributing to the understanding of the mechanistic basis of human biology and disease.

You trained as an evolutionary biologist. What triggered your interest in this field and then into genomics?

In my younger days, I was interested in birds, learning to identify them and track their migration. In college, I was part of a team doing regional surveys of the distribution and biodiversity of reptiles and amphibians, and I was engaged in early investigations into rare and endangered  local species.

Although my initial graduate work studied chromosomal genetics of the fruit-fly, I funded the later part of my graduate degree working as an interpretive naturalist for the State of Rhode Island (USA), giving field talks on everything from ‘The Edible Seashore’ to the ‘Sex Lives of Invertebrates’.

A key influence on my career was my graduate mentor, Dr Ernest Williams, Agassiz Professor of Zoology at Harvard University. He alerted me to the confluence of my interests in classification of species in the natural world with my interest in the genetics and genomics of evolution and particularly in understanding the processes of speciation.

I brought my molecular biology skill set to the study of hybrid zones and speciation among lizard groups in the Caribbean. The key to all was the grounding of my molecular investigations in the reflections of that work in natural systems.

What do you most enjoy about your current work?

Most of my work now is in the development of biomedical ontologies and data integration standards to facilitate and support computational data analysis. What I like most is the global interest and effort to succinctly and cooperatively organize this information with the objective of bringing this experimental information to a network of investigators to understand new aspects of molecular and genomic systems.

I like organizing information and seeing patterns. I recognize that my brain wants to find patterns and correlations, so I have to be careful with my analyses to confirm that the signal I’m seeing is real. I find this era of data science and comparative genomic analyses to be a challenging and exciting time to work in.

Please tell us about one of the recent articles you recommended on F1000Prime, why you picked it, and how it fits into the current research landscape?

I picked an article published in Science by Lixin Chen et al. on DNA damage as a cause of sequencing errors because of the issue of understanding the data, how it is generated, and what the caveats are. Variant identification and impact are hugely important in our efforts to understand human disease mechanisms, but often we don’t fully investigate the origin of the data in front of us.

This is the ‘data in’ problem. With all our computation tools, one can enter a dataset, and some data analysis result will spit out. However, if the data in is faulty, we mislead ourselves and confuse our scientific understanding. I advocate for great caution when evaluating input data sets. Then we can spend our energy testing the analysis algorithms and reporting our results.

Today is International Women’s Day, what advice would you give to women who are thinking about pursuing a career in STEM based on what you have experienced during your career?

My advice would be to keep following your interests and don’t overthink novel opportunities. New ways of understanding our world are emerging, and such knowledge is often the result of stepping away from the most travelled path of investigation.

When I started in bioinformatics and computational biology, during the early days of the human genome project, these areas were hardly recognised as domains of scientific research. Yet because of the work in these areas at the beginning of  the development of the Internet and Web, we now have amazing access to data and data investigations not even conceptualised back then. The data being generated required new ways of data organisation and analysis. I feel fortunate to have followed my opportunities to be engaged in this work that interested me.