Contact: Cherie Winner, 509-335-4846, cwinner@wsu.edu
It's Only a Model
Richard Gomulkiewicz and Patrick Carter are among dozens of researchers at Washington State University creating models to explore challenging problems.
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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