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, he saw that diabetes was indeed emerging,
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, even though he showed no symptoms.
Snyder’s story illustrates the power of looking beyond the genome,
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, 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, and numerous superimposed data sources give a whole lot of detailed, real-time information. With a few taps, Google Maps can show how to get across Boston at rush hour,
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, 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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