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Protein engineering

Accelerating protein sensor optimization with machine learning

Nature Computational Science volume 4, pages 165–166 (2024)Cite this article

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A recent study introduces a machine learning approach to investigate the effects of mutations on protein sensors commonly employed in fluorescence microscopy, thus enabling the discovery of high-performance sensors.

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Fig. 1: Machine-learning-based optimization of calcium sensor performance.

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Authors and Affiliations

  1. Department of Neurosciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA

    Hod Dana

  2. Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, School of Medicine, Case Western Reserve University, Cleveland, OH, USA

    Hod Dana

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  1. Hod Dana
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Correspondence to Hod Dana.

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The author declares no competing interests.

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Dana, H. Accelerating protein sensor optimization with machine learning. Nat Comput Sci 4, 165–166 (2024). https://doi.org/10.1038/s43588-024-00612-9

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