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Building a two-way street between cell biology and machine learning

Nature Cell Biology volume 26, pages 13–14 (2024)Cite this article

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With biomedical sciences quickly outgrowing many other application areas in terms of data generation, there is a unique opportunity for life sciences to become one of the greatest beneficiaries of research in machine learning and AI, and also inspire foundational developments in it.

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Acknowledgements

C.U. was partially supported by the Office of Naval Research (N00014-22-1-2116), National Center for Complementary and Integrative Medicine/National Institutes of Health (1DP2AT012345), and a Simons Investigator Award.

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Authors and Affiliations

  1. Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Caroline Uhler

  2. Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA

    Caroline Uhler

  3. Institute for Data, Systems, and Society, MIT, Cambridge, MA, USA

    Caroline Uhler

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  1. Caroline Uhler
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Correspondence to Caroline Uhler.

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Competing interests

C.U. directs the Eric and Wendy Schmidt Center at the Broad Institute. She serves on the scientific advisory board of Immunai, Relation Therapeutics and Focal Biosciences, and receives research funding from AstraZeneca and Janssen Pharmaceuticals.

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Uhler, C. Building a two-way street between cell biology and machine learning. Nat Cell Biol 26, 13–14 (2024). https://doi.org/10.1038/s41556-023-01279-6

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