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AI in Action: Combing the genome for the roots of autism

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Science  07 Jul 2017:
Vol. 357, Issue 6346, pp. 25
DOI: 10.1126/science.357.6346.25

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Summary

For geneticists, autism is a vexing challenge. Inheritance patterns suggest it has a strong genetic component. But variants in scores of genes known to play some role in autism can explain only about 20% of all cases. Finding other variants that might contribute requires looking for clues in data on the 25,000 other human genes and their surrounding DNA—an overwhelming task for human investigators. So computational biologists have enlisted the tools of artificial intelligence (AI), which can ask a trillion questions where scientists can ask only 10. First, these researchers combined hundreds of genomics data sets and used machine learning build a map of gene interactions. They compared those of the few well-established autism risk genes with those of thousands of other unknown genes and last year flagged another 2500 genes likely to be involved in this disorder. Now they have developed a deep learning tool to find non-coding DNA that may also play a role in autism and other diseases.