CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images.
Cryo-electron Microscopy
Neural Scene Representation
Journal
Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision
Titre abrégé: Comput Vis ECCV
Pays: Germany
ID NLM: 101151802
Informations de publication
Date de publication:
Oct 2022
Oct 2022
Historique:
entrez:
6
2
2023
pubmed:
7
2
2023
medline:
7
2
2023
Statut:
ppublish
Résumé
Cryo-electron microscopy (cryo-EM) has become a tool of fundamental importance in structural biology, helping us understand the basic building blocks of life. The algorithmic challenge of cryo-EM is to jointly estimate the unknown 3D poses and the 3D electron scattering potential of a biomolecule from millions of extremely noisy 2D images. Existing reconstruction algorithms, however, cannot easily keep pace with the rapidly growing size of cryo-EM datasets due to their high computational and memory cost. We introduce cryoAI, an
Identifiants
pubmed: 36745134
doi: 10.1007/978-3-031-19803-8_32
pmc: PMC9897229
mid: NIHMS1824058
doi:
Types de publication
Journal Article
Langues
eng
Pagination
540-557Subventions
Organisme : NIGMS NIH HHS
ID : R01 GM144965
Pays : United States
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