Cargando…
Deep Learning to Predict Protein Backbone Structure from High-Resolution Cryo-EM Density Maps
Cryo-electron microscopy (cryo-EM) has become a leading technology for determining protein structures. Recent advances in this field have allowed for atomic resolution. However, predicting the backbone trace of a protein has remained a challenge on all but the most pristine density maps (<2.5 Å r...
Autores principales: | Si, Dong, Moritz, Spencer A., Pfab, Jonas, Hou, Jie, Cao, Renzhi, Wang, Liguo, Wu, Tianqi, Cheng, Jianlin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063051/ https://www.ncbi.nlm.nih.gov/pubmed/32152330 http://dx.doi.org/10.1038/s41598-020-60598-y |
Ejemplares similares
-
The Local Resolution of Cryo-EM Density Maps
por: Kucukelbir, Alp, et al.
Publicado: (2013) -
Beyond the Backbone: The Next Generation of Pathwalking Utilities for Model Building in CryoEM Density Maps
por: Hryc, Corey F., et al.
Publicado: (2022) -
AlphaFold2 and CryoEM: Revisiting CryoEM modeling in near-atomic resolution density maps
por: Hryc, Corey F., et al.
Publicado: (2022) -
DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes
por: Pfab, Jonas, et al.
Publicado: (2021) -
Density modification of cryo-EM maps
por: Terwilliger, Thomas C., et al.
Publicado: (2020)