Evidence map›Paper›PMID 26592709›Full record

ArticleJournal of structural biology2016

Gctf: Real-time CTF determination and correction.

Kai Zhang

Abstract read
In one paragraph

Article in Journal of structural biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2,497 papers.

0numbers the graph read from it
0cells of the map it votes in
2,497citing 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

2,497 citing papers in PubMed.

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  12. Vesicle-associated exudates fromApplied and environmental microbiology · 2026
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  13. Mechanistic Basis for 5-HTNature communications · 2026
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2,437 more citing papers are in PubMed but not listed here.

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

1 author.

Kai ZhangMedical Research Council Laboratory of Molecular Biology, Division of Structural Studies, Francis Crick Avenue, Cambridge CB2 0QH, UK. Electronic address: kzhang@mrc-lmb.cam.ac.uk.

Funding

Medical Research Council MC_UP_A025_1011Wellcome Trust 100387
6 · The paper itself

Abstract

Accurate estimation of the contrast transfer function (CTF) is critical for a near-atomic resolution cryo electron microscopy (cryoEM) reconstruction. Here, a GPU-accelerated computer program, Gctf, for accurate and robust, real-time CTF determination is presented. The main target of Gctf is to maximize the cross-correlation of a simulated CTF with the logarithmic amplitude spectra (LAS) of observed micrographs after background subtraction. Novel approaches in Gctf improve both speed and accuracy. In addition to GPU acceleration (e.g. 10-50×), a fast '1-dimensional search plus 2-dimensional refinement (1S2R)' procedure further speeds up Gctf. Based on the global CTF determination, the local defocus for each particle and for single frames of movies is accurately refined, which improves CTF parameters of all particles for subsequent image processing. Novel diagnosis method using equiphase averaging (EPA) and self-consistency verification procedures have also been implemented in the program for practical use, especially for aims of near-atomic reconstruction. Gctf is an independent program and the outputs can be easily imported into other cryoEM software such as Relion (Scheres, 2012) and Frealign (Grigorieff, 2007). The results from several representative datasets are shown and discussed in this paper.

Indexed as

SoftwareAlgorithmsCryoelectron MicroscopyImage Processing, Computer-AssistedImaging, Three-DimensionalContrast transfer functionCryo-electron microscopyCTF determinationGPU program

Identifiers

PMID26592709
PMCPMC4711343

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.