Accelerating protein sensor optimization with machine learning

Hod Dana

doi:10.1038/s43588-024-00612-9

2024-03-21

PRE

Hod Dana *

DOI：10.1038/s43588-024-00612-9

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摘要

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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.

期刊

Nature Computational Science

IF:

18.3

论文数:

3.1K

被引数:

4.0K

机构

cleveland clinic foundation

学者数:

3.7W

论文数: 3.0W

被引数: 29

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