Evidence map›Paper›PMID 34437529›Full record

ArticlePLoS biology2021

Step-by-step guide to efficient subtomogram averaging of virus-like particles with Dynamo.

Stefano Scaramuzza, Daniel Castaño-Díez

Abstract readValidation Study
In one paragraph

Article in PLoS biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

  1. Article
  2. Article
  3. Diel remodeling and cellular integration of the nitroplast.bioRxiv : the preprint server for biology · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. The big chill: Growth ofQRB discovery · 2024
    Review
  13. Integrative Approaches to Study Virus Structures.Sub-cellular biochemistry · 2024
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Computational methods forFrontiers in cellular and infection microbiology · 2023
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Stefano ScaramuzzaBioEM Lab, Biozentrum, University of Basel, Basel, Switzerland.ORCID 0000-0002-5856-5894
Daniel Castaño-DíezBioEM Lab, Biozentrum, University of Basel, Basel, Switzerland.ORCID 0000-0002-0197-163X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Subtomogram averaging (STA) is a powerful image processing technique in electron tomography used to determine the 3D structure of macromolecular complexes in their native environments. It is a fast growing technique with increasing importance in structural biology. The computational aspect of STA is very complex and depends on a large number of variables. We noticed a lack of detailed guides for STA processing. Also, current publications in this field often lack a documentation that is practical enough to reproduce the results with reasonable effort, which is necessary for the scientific community to grow. We therefore provide a complete, detailed, and fully reproducible processing protocol that covers all aspects of particle picking and particle alignment in STA. The command line-based workflow is fully based on the popular Dynamo software for STA. Within this workflow, we also demonstrate how large parts of the processing pipeline can be streamlined and automatized for increased throughput. This protocol is aimed at users on all levels. It can be used for training purposes, or it can serve as basis to design user-specific projects by taking advantage of the flexibility of Dynamo by modifying and expanding the given pipeline. The protocol is successfully validated using the Electron Microscopy Public Image Archive (EMPIAR) database entry 10164 from immature HIV-1 virus-like particles (VLPs) that describe a geometry often seen in electron tomography.

Indexed as

Electron Microscope TomographySoftwareImage Processing, Computer-Assisted

Identifiers

PMID34437529
PMCPMC8389376

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.