This year marks the 100th anniversary of the journal GENETICS, a foundational journal in the field. To mark the occasion, a group of geneticists including Stanford's Jonathan Pritchard, PhD, have taken time to explore the history of genetics research. Specifically, members of Pritchard’s lab have mined all the papers published in GENETICS since its inception to find drivers of scientific innovation.
Graduate student Natalie Telis is first author on the resulting paper, published in GENETICS. She primarily studies the genetics of recent human evolution, but her side projects often leverage data to learn about how science happens. I spoke with her about the work recently.
How did this project start?
In the Pritchard Lab, we happened to have a huge database of information we’d computed on published papers and how they were related to each other. So, we had this idea of doing something quantitative with the text of articles published in GENETICS to learn about the history of the field.
How did you analyze the papers in your database?
We started really broad — when and where these papers come from and the rate at which they’re published. From that, we were able see geographic changes in who does genetics. In the 1950s, there’s a big expansion in genetics research in the U.S., but in the 1980s, probably because of the internet, we see genetics expand worldwide, especially in East Asia.
We also compared words that are more or less common from one decade to the next. This showed us shifts in model organism usage. For example, we were obsessed with corn for like 30 years and then it went out of vogue. Humans, on the other hand, don’t start getting written about until you have National Institutes of Health funding to study them. Similarly, a lot of techniques pop up and then crash out as new methods replace them.
Are there any general lessons from these findings?
In the 1950s alone, you see a doubling in the number of genetics publications. You also start seeing this lightning turnover where new techniques are coming out – one decade does not look like the next.
At the same time, right around the late 1940s, you get the GI bill, the National Science Foundation starting up and funding genetics, and the National Institutes of Health appropriating money for genetics. So we think one of the biggest things that affects innovation and the rate of papers being published is funding.
Why are these kinds of studies important?
The trends we find are intuitive. But one of the really powerful things about being a scientist is confirming things that are true rather than making 'handwave-y' guesses. Using these databases and good statistical techniques, I can tell you: 'this is the year that this trend becomes significant.' And I think it’s a powerful way to create takeaways for other fields. It’s nice to be able to say 'here you give them funding; here innovation begins.'
Also, because we’re now in the data science age, the ability to do genuinely quantitative meta-science with numbers that are too large to ignore is now at our fingertips.
Is this kind of “science about science” going to change the way we do and think about research?
I hope that it is. I recognize that there are many important, fundamental scientific questions. I think that genetics is really cool, but have we thought about global warming? That sounds hard. And if we could figure out what magic allowed geneticists to come up with a bunch of crazy techniques in the 1950s and ‘60s, maybe we could apply that magic to other fields.
Emily Glassberg is a graduate student with Jonathan Pritchard and Marc Feldman and is a producer of the Goggles Optional podcast.
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