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on the value of computer modeling
How would you define computational medicine?
WINSLOW: It’s applying methods from engineering, mathematics and computational sciences to improve our understanding and treatment of human diseases.
Do biomedical researchers broadly accept the concept?
WINSLOW: It depends on the application. Both clinicians and basic researchers see the need to use modern statistical theory to understand the complexity of large-scale biomedical data. They also understand the need to quantify the changes in anatomy that underlie disease because it’s so helpful in interpreting modern imaging data. The more controversial area is modeling disease processes.
Why is that?
WINSLOW: Biologists understandably think experimentation is the most important thing. Of course, it will always be needed, but today we need the interplay between experiment, theory and modeling. Modeling can enhance experimentation. We need models to make predictions, and we need experiments to test the predictions made by the models.
What’s your biggest challenge in getting the Institute for Computational Medicine up and running?
WINSLOW: Our mission is to bring in very strong theoretical and computational people. Because they’ll mostly be based in engineering departments, the challenge for us is to connect their skills with real applications—and collaborators—in the School of Medicine. We have strong existing relationships there—Professor of genetic medicine, Aravinda Chakravarti, for example, co-directs our institute. But we’re also actively recruiting affiliate faculty, biomedical researchers who see value in what we do and who want to collaborate with us in bringing theory and computation to their problems.