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Technology Feature | Translating big data: The proteomics challenge

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Science  15 Jun 2018:
Vol. 360, Issue 6394, pp. 1255
DOI: 10.1126/science.360.6394.1255-b


Getting the most out of protein-related information depends on teamwork among scientists around the world, and that involves sharing large datasets. Simply passing big data back and forth is not a problem, however—the main obstacle is sharing that data in a way that other scientists can use it. Building software that can interpret information from different experiments and equipment remains complicated; likewise, exploring and analyzing large datasets from proteomics experiments even from one lab requires software that is most often developed in-house.

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