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Although new super-resolution imaging techniques provide valuable biological insights, some applications, such as determining the organization of neural projections in the brain, are better served by comprehensive imaging of very large samples at lower resolution.
As the gap between the amount of data and the tools for analysis continues to grow, biologists are looking to mathematical modeling to turn data sets into biology. This is bad news for those who studied biology to avoid mathematics—but take heart, the tools are getting better and easier to use, and the best of them are now being used in some inspiring ways. Steven Buckingham reports.