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NEW YORK (GenomeWeb) – A pair of studies published last month in Nature Methods suggest growing momentum for the use of deep learning approaches for proteomic data analysis.

Working independently, a team led by researchers at the Max Planck Institute of Biochemistry and Verily and a team led by researchers at the Technical University of Munich (TUM) developed deep learning tools for predicting patterns of ion fragmentation in mass spec-based proteomics.

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The Washington Post reports that a US Senate committee voted this week to approve the nomination of Stephen Hahn to lead the Food and Drug Administration.

Nature News reports that gene therapy approaches are tackling sickle cell disease, but that the cost of treatment is a concern.

One gene regulates hundreds of others to influence facial development, according to New Scientist.

In Nature this week: resources for single-cell analysis, little overlap in the microRNAs used by Salmonella and Shigella to infect host cells, and more.