Evidence map›Paper›PMID 38510167›Full record

ArticleBiological imaging2023

Signal enhancement for two-dimensional cryo-EM data processing.

Guy Sharon, Yoel Shkolnisky, Tamir Bendory

Abstract read
In one paragraph

Article in Biological imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Guy SharonSchool of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel.
Yoel ShkolniskySchool of Mathematical Sciences, Tel Aviv University, Tel Aviv, Israel.ORCID https://orcid.org/0000-0001-8784-3753
Tamir BendorySchool of Electrical Engineering, Tel Aviv University, Tel Aviv, Israel.ORCID https://orcid.org/0000-0003-2373-9388

Funding

Reconstruction of heterogeneous and small macromolecules by cyro-EMR01GM136780 · NIGMS · PRINCETON UNIVERSITY · PI SINGER, AMIT · 2020 to 2023
$1.3M
NIGMS NIH HHS R01 GM136780
6 · The paper itself

Abstract

Different tasks in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM) require enhancing the quality of the highly noisy raw images. To this end, we develop an efficient algorithm for signal enhancement of cryo-EM images. The enhanced images can be used for a variety of downstream tasks, such as two-dimensional classification, removing uninformative images, constructing ab initio models, generating templates for particle picking, providing a quick assessment of the data set, dimensionality reduction, and symmetry detection. The algorithm includes built-in quality measures to assess its performance and alleviate the risk of model bias. We demonstrate the effectiveness of the proposed algorithm on several experimental data sets. In particular, we show that the quality of the resulting images is high enough to produce ab initio models of Å resolution. The algorithm is accompanied by a publicly available, documented, and easy-to-use code.

Indexed as

2D classificationCryo-electron microscopysignal enhancement

Identifiers

PMID38510167
PMCPMC10951933

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.