Cargando…
EPicker is an exemplar-based continual learning approach for knowledge accumulation in cryoEM particle picking
Deep learning is a popular method for facilitating particle picking in single-particle cryo-electron microscopy (cryo-EM), which is essential for developing automated processing pipelines. Most existing deep learning algorithms for particle picking rely on supervised learning where the features to b...
Autores principales: | Zhang, Xinyu, Zhao, Tianfang, Chen, Jiansheng, Shen, Yuan, Li, Xueming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9072698/ https://www.ncbi.nlm.nih.gov/pubmed/35513367 http://dx.doi.org/10.1038/s41467-022-29994-y |
Ejemplares similares
-
AlphaFold2 and CryoEM: Revisiting CryoEM modeling in near-atomic resolution density maps
por: Hryc, Corey F., et al.
Publicado: (2022) -
Routine single particle CryoEM sample and grid characterization by tomography
por: Noble, Alex J, et al.
Publicado: (2018) -
Reducing effects of particle adsorption to the air-water interface in cryoEM
por: Noble, Alex J., et al.
Publicado: (2018) -
Emerging Themes in CryoEM—Single Particle Analysis
Image Processing
por: Vilas, Jose Luis, et al.
Publicado: (2022) -
Time-resolved cryoEM using Spotiton
por: Dandey, Venkata P., et al.
Publicado: (2020)