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High-Throughput Cryo-EM Enabled by User-Free Preprocessing Routines.
- Source :
-
Structure (London, England : 1993) [Structure] 2020 Jul 07; Vol. 28 (7), pp. 858-869.e3. Date of Electronic Publication: 2020 Apr 14. - Publication Year :
- 2020
-
Abstract
- Single-particle cryoelectron microscopy (cryo-EM) continues to grow into a mainstream structural biology technique. Recent developments in data collection strategies alongside new sample preparation devices herald a future where users will collect multiple datasets per microscope session. To make cryo-EM data processing more automatic and user-friendly, we have developed an automatic pipeline for cryo-EM data preprocessing and assessment using a combination of deep-learning and image-analysis tools. We have verified the performance of this pipeline on a number of datasets and extended its scope to include sample screening by the user-free assessment of the qualities of a series of datasets under different conditions. We propose that our workflow provides a decision-free solution for cryo-EM, making data preprocessing more generalized and robust in the high-throughput era as well as more convenient for users from a range of backgrounds.<br />Competing Interests: Declaration of Interests The authors declare no competing interests.<br /> (Copyright © 2020 Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1878-4186
- Volume :
- 28
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- Structure (London, England : 1993)
- Publication Type :
- Academic Journal
- Accession number :
- 32294468
- Full Text :
- https://doi.org/10.1016/j.str.2020.03.008