Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning

Traces from single-molecule fluorescence microscopy (SMFM) experiments exhibit photophysical artifacts that typically make analysis time-consuming. Here, the authors have developed an easily accessible software, AutoSiM, for two distinct applications of deep learning to the efficient processing of S...

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Auteurs principaux: Jieming Li, Leyou Zhang, Alexander Johnson-Buck, Nils G. Walter
Format: article
Langue:EN
Publié: Nature Portfolio 2020
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Accès en ligne:https://doaj.org/article/e41c9c9671084acbbaf16ef58f178d60
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