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Go Figure

JULIE MITCHELL, an assistant professor of biochemistry and mathematics, builds computational tools that help biologists analyze and predict changes to protein structures that will alter their function–information that can help scientists design novel drugs and disease-fighting aagents. Describing herself as a liaison between the logic-driven world of math and the chaotic realm of biology, Mitchell has collaborated with researchers working on everything from cancer to better processes for making ethanol.

How different are mathematics and biology anyway?

In many ways, mathematics and biology are almost logical opposites. Mathematics is more of an art: You create rules for some geometric or algebraic space, and then you see what you can prove about it. In biology, we can’t even figure out what some of the basic rules are. There are no theorems. Everything has a little asterisk that says: except in these following cases. And so, as a mathematician, if you want to go into biology, you have to be able to accept that and not allow it to drive you insane.

Is that how you came into this field, as a mathematician?

Yes, I graduated with my math degree in 1998 from UC-Berkeley.

What was it that attracted you to biology and proteins?

My background is in geometric analysis, so what drew me to proteins in the first place was their interesting shapes. Some people look at proteins mainly as strings of amino acids, and when they think about what we call a point mutation—a change to a single amino acid—to them that’s a change in the linear sequence. I don’t quite think that way. To me, that’s a structural change, a geometric change, as well as a change in the protein’s biochemical properties.

Mathematics and statistics can help uncover patterns in biological systems.

Now for a long time, I think I translated chemistry into mathematics through physics. You know, everything is a bunch of atoms, here are the forces on the atoms, and so on. That can be a starting point, but ultimately you have to begin thinking a bit more like a biochemist—which takes a lot of time.

How did you begin to do that, to think more like a biochemist?

(laughing) I think trial by fire. When I first switched fields, the most helpful thing I did was not to take classes or read books, but to attend a lot of professional meetings and go to the talks and, especially, the poster sessions. That’s where the graduate students and postdocs are representing their papers, and you feel a little less intimidated saying, “I know this is a really dumb question, but what does that mean?”
Not being afraid to ask a dumb question is very important. You have to be very brave and humble, in a way, to admit when you don’t know something. At the same time, you have to be very good at—how shall I say this?—pretending to know what you’re talking about when you half-don’t (laughing).

It truly does sound like trial by fire. Why go through it?

When I was finishing up my Ph.D., I really loved mathematics, but I didn’t feel a tangible connection between the work I was doing and the real world. Mathematics was beautiful, it was fascinating, but I felt like I wanted to have a more immediate impact.
Eventually, I was pointed toward the protein-folding problem, and so I got on the Internet and typed in “protein folding.” And then I pulled up pictures of these fabulous proteins, with all of these interesting coiled structures, all wrapped up into a compact little ball. And there were partial differential equations and dynamical systems that went along with these fascinating geometric structures, and from that point on, that’s what I was doing.