Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning
oleh: Jieming Li, Leyou Zhang, Alexander Johnson-Buck, Nils G. Walter
| Format: | Article |
|---|---|
| Diterbitkan: | Nature Portfolio 2020-11-01 |
Deskripsi
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 SMFM time traces.