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CHICAGO (GenomeWeb) – Evidence published in the journal Nature Biotechnology in September demonstrated the efficacy of DeepVariant, Google's deep-learning-based variant caller, compared to older previous methods of calling genomic variants.

DeepVariant "replaces the assortment of statistical modeling components with a single deep-learning model," according to the paper, whose authors represented Google and sister company Verily.

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The Hill reports President Donald Trump issued an executive directing federal agencies to cut the number of board and advisory committees they have.

The New York Times reports that researchers are combining tools to more quickly develop crops to feed a growing population and cope with shifting climates.

Scientists in Canada are looking to the UK's plan to sequence children with rare conditions for inspiration, the National Post reports.

In PNAS this week: copy number changes arose during polar bear evolution, genomic and transcriptomic analysis of the Siberian hamster, and more.