DeepFRAP: Fast fluorescence recovery after photobleaching data analysis using deep neural networks

Conventional analysis of fluorescence recovery after photobleaching (FRAP) data for diffusion coefficient estimation typically involves fitting an analytical or numerical FRAP model to the recovery curve data using non‐linear least squares. Depending on the model, this can be time consuming, especia...

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Detalles Bibliográficos
Autores principales: Wåhlstrand Skärström, Victor, Krona, Annika, Lorén, Niklas, Röding, Magnus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248438/
https://www.ncbi.nlm.nih.gov/pubmed/33247838
http://dx.doi.org/10.1111/jmi.12989

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248438/
https://www.ncbi.nlm.nih.gov/pubmed/33247838
http://dx.doi.org/10.1111/jmi.12989

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