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New tools for automated high-resolution cryo-EM structure determination in RELION-3
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Abstract
Here, we describe the third major release of RELION. CPU-based vector acceleration has been added in addition to GPU support, which provides flexibility in use of resources and avoids memory limitations. Reference-free autopicking with Laplacian-of-Gaussian filtering and execution of jobs from python allows non-interactive processing during acquisition, including 2D-classification, de novo model generation and 3D-classification. Per-particle refinement of CTF parameters and correction of estimated beam tilt provides higher resolution reconstructions when particles are at different heights in the ice, and/or coma-free alignment has not been optimal. Ewald sphere curvature correction improves resolution for large particles. We illustrate these developments with publicly available data sets: together with a Bayesian approach to beam-induced motion correction it leads to resolution improvements of 0.2–0.7 Å compared to previous RELION versions.
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Metadata
- Authors
- Zivanov, J., Nakane, T., Forsberg, B. O., Kimanius, D., Hagen, W. J., Lindahl, E., & Scheres, S. H.
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2018-11-09
- Volume
- 7
- ISSN
- 2050-084X (ISSN-L)
- OpenAlex
- W2899714098
- Cited by
- 4,621
- References
- 1
- FWCI
- 198.08
- Type
- journal article
- Language
- en
- Open access
- gold
- Licence
- creativecommons.org/licenses/by/4.0/ (vor)
- creativecommons.org/licenses/by/4.0/ (am)
- creativecommons.org/licenses/by/4.0/ (tdm)
- Funders
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (SNF: P2BSP2 168735)
- Japan Society for the Promotion of Science (Overseas Research Fellowship)
- Swedish National Infrastructure for Computing (2017/12-54)
- Vetenskapsrådet (2017-04641)
- Knut och Alice Wallenbergs Stiftelse
- Medical Research Council (MC_UP_A025_1013)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
