Cargando…
The evolution of SPHIRE-crYOLO particle picking and its application in automated cryo-EM processing workflows
Particle selection is a crucial step when processing electron cryo microscopy data. Several automated particle picking procedures were developed in the past but most struggle with non-ideal data sets. In our recent Communications Biology article, we presented crYOLO, a deep learning based particle p...
Autores principales: | Wagner, Thorsten, Raunser, Stefan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7012881/ https://www.ncbi.nlm.nih.gov/pubmed/32047248 http://dx.doi.org/10.1038/s42003-020-0790-y |
Ejemplares similares
-
Two particle-picking procedures for filamentous proteins: SPHIRE-crYOLO filament mode and SPHIRE-STRIPER
por: Wagner, Thorsten, et al.
Publicado: (2020) -
SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM
por: Wagner, Thorsten, et al.
Publicado: (2019) -
TranSPHIRE: automated and feedback-optimized on-the-fly processing for cryo-EM
por: Stabrin, Markus, et al.
Publicado: (2020) -
A self-supervised workflow for particle picking in cryo-EM
por: McSweeney, Donal M., et al.
Publicado: (2020) -
High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE
por: Moriya, Toshio, et al.
Publicado: (2017)