Evidence map›Paper›PMID 41773507›Full record

ArticleActa crystallographica. Section D, Structural biology2026

Decision-making in serial crystallography: a simple test to quickly determine whether sufficient data have been collected.

David von Stetten, Arwen R Pearson

Abstract read
In one paragraph

Article in Acta crystallographica. Section D, Structural biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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 citing papers in PubMed.

  1. Article
  2. Article
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.

David von StettenEuropean Molecular Biology Laboratory (EMBL), Notkestrasse 85, 22760 Hamburg, Germany.ORCID 0000-0001-7906-9788
Arwen R PearsonInstitute for Nanostructure and Solid State Physics, Hamburg Centre for Ultrafast Imaging, University of Hamburg, HARBOR Building 610, Luruper Chaussee 149, 22761 Hamburg, Germany.ORCID 0000-0001-8499-7490

Funding

Bundesministerium für Bildung und Forschung 05K16GU1Bundesministerium für Bildung und Forschung 05K19GU1Bundesministerium für Bildung und Forschung 05K22GU6
6 · The paper itself

Abstract

In standard rotational data collection for macromolecular crystallography, data are normally collected from a single crystal, and the resulting data processing delivers metrics for data completeness and signal to noise that are well established. However, in serial crystallography it can be difficult to assess quickly whether enough data have been recorded to deliver a well scaled and complete dataset with sufficient signal to noise to address the scientific question being asked. Completeness alone is not an appropriate metric, as a nominally complete dataset can be obtained with a much smaller number of images, and thus multiplicity, than is needed to produce a final dataset with well estimated merged intensity values. Insufficient data result in alarmingly reasonable processing statistics and plausible electron-density maps that contain almost no experimental signal, instead being dominated by the phases from the phasing model. We have therefore established a simple electron-density-based test to determine whether enough data have been collected, and implemented this in the autoprocessing pipeline at the T-REXX endstation on beamline P14 at PETRA III. Importantly, the results of this perturbed model real-space difference density (PMRDD) test help to guide decisions as to whether more data should be collected or whether the experimenter can move onto a new time-point or sample.

Indexed as

Data CollectionMacromolecular SubstancesCrystallography, X-RayModels, MolecularMacromolecular Substancesmacromolecular crystallographyserial crystallographysignal to noisetime-resolved crystallography

Identifiers

PMID41773507
PMCPMC12954858

What OpenQuestion holds

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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.