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Researchers Want to Link Your Genes and IncomeShould They?

The UK Biobank is the single largest public genetic repository in the world, with samples of the genetic blueprints of half a million Brits standing by for scientific study. But when David Hill, a statistical geneticist at the University of Edinburgh, went poring through that data, he wasn’t looking for a cure for cancer or deeper insights into the biology of aging. Nothing like that. He was trying to figure out why some people make more money than others. Along with a team of European collaborators, Hill sifted through the…

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DNA Crime-Solving Is Still New, Yet It May Have Gone Too Far

DNA is one of the most powerful substances in the universe. In the same structure it can encode the instructions to make uranium-munching microbes, giant flying lizards, or a stand of quaking aspens five miles wide. It can store every movie ever made in a single test tube. And it can stick around for tens of thousands of years. Just this week, Japanese scientists revealed they’d awakened some ancient wooly mammoth DNA by sticking it into mice embryos. What is dead may never die, indeed. It’s DNA’s ability to resurrect…

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23andMe’s Pharma Deals Have Been the Plan All Along

Since the launch of its DNA testing service in 2007, genomics giant 23andMe has convinced more than 5 million people to fill a plastic tube with half a teaspoon of saliva. In return for all that spit (and some cash too), customers get insights into their biological inheritance, from the superficial—do you have dry earwax or wet?—to mutations associated with disease. What 23andMe gets is an ever-expanding supply of valuable behavioral, health, and genetic information from the 80 percent of its customers who consent to having their data used for…

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Can Machine Learning Find Medical Meaning in a Mess of Genes?

“We don’t have much ground truth in biology.” According to Barbara Engelhardt, a computer scientist at Princeton University, that’s just one of the many challenges that researchers face when trying to prime traditional machine-learning methods to analyze genomic data. Techniques in artificial intelligence and machine learning are dramatically altering the landscape of biological research, but Engelhardt doesn’t think those “black box” approaches are enough to provide the insights necessary for understanding, diagnosing and treating disease. Instead, she’s been developing new statistical tools that search for expected biological patterns to map…

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