Machine learning for cluster analysis of localization microscopy data

Quantifying the extent to which points are clustered in single-molecule localization microscopy data is vital to understanding the spatial relationships between molecules in the underlying sample. Many existing computational approaches are limited in their ability to process large-scale data sets, t...

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Detalles Bibliográficos
Autores principales: Williamson, David J., Burn, Garth L., Simoncelli, Sabrina, Griffié, Juliette, Peters, Ruby, Davis, Daniel M., Owen, Dylan M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083906/
https://www.ncbi.nlm.nih.gov/pubmed/32198352
http://dx.doi.org/10.1038/s41467-020-15293-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083906/
https://www.ncbi.nlm.nih.gov/pubmed/32198352
http://dx.doi.org/10.1038/s41467-020-15293-x

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