Abstract
Optimizing genetically encoded fluorescent indicators (GEFIs) is intellectually and experimentally taxing. We developed a machine learning (ML) platform to discover new variants of the calcium indicator GCaMP and illustrate ML’s ability to accelerate GEFI engineering.
© 2023 The Author(s)
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