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  It’s only a model      

 

by Cherie Winner
photography by Robert Hubner

Carter & Gomulkiewicz

Mouse meets math: Richard Gomulkiewicz and Patrick Carter use athletic mice and advanced mathematics to study how we inherit the ability and desire to exercise.

 

Winter 2005-06 

There’s a scene in the movie Monty Python and the Holy Grail where the stalwart heroes first behold the castle of Camelot. Their awe at its size and beauty abruptly ends when one of them points out, “It’s only a model.”

Patrick Carter loves that scene. The Washington State University biologist hears the same thing from his students all the time.

“Ninety-nine percent of undergrads and beginning grad students will pooh-pooh models,” he says, “when in fact, virtually everything that they know as facts in biology is model-based.”

From the structure of the atom to how memory works, models permeate science. Carter says even he didn’t fully appreciate that until a few years ago, when he started working with mathematician Richard Gomulkiewicz on a model of how exercise behavior is inherited. Now he enthusiastically points out models that are so deeply embedded in our minds that most of us don’t realize they’re there.

He offers an example. Our DNA has a double-helix structure that looks something like a twisted ladder. Right?

“The evidence is overwhelming that that’s true,” says Carter. “But that understanding is all model-based. No one’s ever seen it.”

Gomulkiewicz says modeling is built into the way science works.

 “You don’t just blindly gather data, ever,” he says. “You’ve got some model in your mind that you’re investigating. We’re all modelers.”

A conceptual model, such as our mental image of the DNA spiral, helps frame research questions and make general predictions. A numerical model uses math or statistics to describe the image and make quantitative predictions about it.

That sounds abstract, but models are judged by a ruthlessly practical standard. A model that consistently makes bad predictions or, worse, no testable predictions at all, gets pitched.

Only a model that consistently makes good predictions becomes part of our way of looking at the world. The model of DNA as a double helix, for instance, matches experimental evidence gathered over decades.

“That’s why we have so much confidence in the model,” says Gomulkiewicz. “It’s done such a great job for us.”


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Dozens of researchers at Washington State University are creating models to explore challenging problems. Here’s a small sampling.
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