Michael Snyder’s genes were telling him that he might be at increased risk for type 2 diabetes. The Stanford University geneticist wasn’t worried: He felt healthy and didn’t have a family history of the disease. But as he monitored other aspects of his own biological data over months and years,
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, he saw that diabetes was indeed emerging, even though he showed no symptoms.
Snyder’s story illustrates the power of looking beyond the genome, the complete catalog of an organism’s genetic information. His tale turns the genome’s one-dimensional view into a multidimensional one. In many ways,
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, a genome is like a paper map of the world. That map shows where the cities are. But it doesn’t say anything about which nations trade with each other,
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, which towns have fierce football rivalries or which states will swing for a particular political candidate.
Open one of today’s digital maps,
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, though,
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, and numerous superimposed data sources give a whole lot of detailed, real-time information. With a few taps,
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, Google Maps can show how to get across Boston at rush hour, offer alternate routes around traffic snarls and tell you where to pick up a pizza on the way.
Now,
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, scientists like Snyder are developing these same sorts of tools for biology,
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, with far-reaching consequences. To figure out what’s really happening within an organism — or within a particular organ or cell — researchers are linking the genome with large-scale data about the output of those genes at

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