Evidence map›Paper›PMID 38487693›Full record

ArticleBiological imaging2023

Ot2Rec: A semi-automatic, extensible, multi-software tomographic reconstruction workflow.

Neville B-Y Yee, Elaine M L Ho, Win Tun, Jake L R Smith, Maud Dumoux, Michael Grange, Michele C Darrow, Mark Basham

Open access · diamondAbstract 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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 98% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 4 institutions in 1 country.

Neville B-Y YeeArtificial Intelligence and Informatics, Rosalind Franklin Institute, Didcot, United Kingdom.ORCID https://orcid.org/0000-0003-0349-3958
Elaine M L HoArtificial Intelligence and Informatics, Rosalind Franklin Institute, Didcot, United Kingdom.ORCID https://orcid.org/0000-0001-8697-4903
Win TunFaculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom.ORCID https://orcid.org/0000-0003-0991-8785
Jake L R SmithStructural Biology, Rosalind Franklin Institute, Didcot, United Kingdom.ORCID https://orcid.org/0000-0003-3234-6228
Maud DumouxStructural Biology, Rosalind Franklin Institute, Didcot, United Kingdom.ORCID https://orcid.org/0000-0002-1732-1041
Michael GrangeStructural Biology, Rosalind Franklin Institute, Didcot, United Kingdom.ORCID https://orcid.org/0000-0003-2580-2299
Michele C DarrowArtificial Intelligence and Informatics, Rosalind Franklin Institute, Didcot, United Kingdom.ORCID https://orcid.org/0000-0001-6259-1684
Mark BashamArtificial Intelligence and Informatics, Rosalind Franklin Institute, Didcot, United Kingdom.ORCID https://orcid.org/0000-0002-8438-1415
Rosalind Franklin Institute · GBCentre for Human Genetics · GBDiamond Light Source · GBMelbourn Science Park · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

Electron cryo-tomography is an imaging technique for probing 3D structures with at the nanometer scale. This technique has been used extensively in the biomedical field to study the complex structures of proteins and other macromolecules. With the advancement in technology, microscopes are currently capable of producing images amounting to terabytes of data per day, posing great challenges for scientists as the speed of processing of the images cannot keep up with the ever-higher throughput of the microscopes. Therefore, automation is an essential and natural pathway on which image processing-from individual micrographs to full tomograms-is developing. In this paper, we present Ot2Rec, an open-source pipelining tool which aims to enable scientists to build their own processing workflows in a flexible and automatic manner. The basic building blocks of Ot2Rec are plugins which follow a unified application programming interface structure, making it simple for scientists to contribute to Ot2Rec by adding features which are not already available. In this paper, we also present three case studies of image processing using Ot2Rec, through which we demonstrate the speedup of using a semi-automatic workflow over a manual one, the possibility of writing and using custom (prototype) plugins, and the flexibility of Ot2Rec which enables the mix-and-match of plugins. We also demonstrate, in the Supplementary Material, a built-in reporting feature in Ot2Rec which aggregates the metadata from all process being run, and output them in the Jupyter Notebook and/or HTML formats for quick review of image processing quality. Ot2Rec can be found at https://github.com/rosalindfranklininstitute/ot2rec.

Indexed as

Cryo-electron microscopycryo-electron tomographyimage processing

Identifiers

PMID38487693
PMCPMC10936412
OpenAlexW4361198908

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.