Evidence map›Paper›PMID 25610625›Full record

ArticleIUCrJ2015

Determination of crystallographic intensities from sparse data.

Kartik Ayyer, Hugh T Philipp, Mark W Tate, Jennifer L Wierman, Veit Elser, Sol M Gruner

Abstract read
In one paragraph

Article in IUCrJ, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. 3D Nanocrystallography and the Imperfect Molecular Lattice.Annual review of physical chemistry · 2024
    Review
  2. Article
  3. SPIND-TC: an indexing method for two-color X-ray diffraction data.Acta crystallographica. Section A, Foundations and advances · 2020
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. EIGER detector: application in macromolecular crystallography.Acta crystallographica. Section D, Structural biology · 2016
    Article
  9. Journal of applied crystallography · 2016
    Article
  10. Article
  11. Article
  12. 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

6 authors.

Kartik AyyerLaboratory of Atomic and Solid State Physics, Cornell University, Ithaca, NY 14853, USA.
Hugh T PhilippLaboratory of Atomic and Solid State Physics, Cornell University, Ithaca, NY 14853, USA.
Mark W TateLaboratory of Atomic and Solid State Physics, Cornell University, Ithaca, NY 14853, USA.
Jennifer L WiermanField of Biophysics, Cornell University, Ithaca, NY 14853, USA ; Cornell High Energy Synchrotron Source (CHESS), Cornell University, Ithaca, NY 14853, USA.
Veit ElserLaboratory of Atomic and Solid State Physics, Cornell University, Ithaca, NY 14853, USA.
Sol M GrunerLaboratory of Atomic and Solid State Physics, Cornell University, Ithaca, NY 14853, USA ; Cornell High Energy Synchrotron Source (CHESS), Cornell University, Ithaca, NY 14853, USA ; Kavli Institute at Cornell for Nanoscale Science, Cornell University, Ithaca, NY 14853, USA.

Funding

Overall (pp. 40-62)P41GM103485 · NIGMS · CORNELL UNIVERSITY · PI CERIONE, RICHARD A. · 2012 to 2018
$15.5M
TRAINING IN MOLECULAR PHYSICS OF BIOLOGICAL SYSTEMST32GM008267 · NIGMS · CORNELL UNIVERSITY ITHACA · PI WANG, MICHELLE D. · 1988 to 2021
$9.6M
NIGMS NIH HHS P41 GM103485NIGMS NIH HHS T32 GM008267
6 · The paper itself

Abstract

X-ray serial microcrystallography involves the collection and merging of frames of diffraction data from randomly oriented protein microcrystals. The number of diffracted X-rays in each frame is limited by radiation damage, and this number decreases with crystal size. The data in the frame are said to be sparse if too few X-rays are collected to determine the orientation of the microcrystal. It is commonly assumed that sparse crystal diffraction frames cannot be merged, thereby setting a lower limit to the size of microcrystals that may be merged with a given source fluence. The EMC algorithm [Loh & Elser (2009 ▶), Phys. Rev. E, 80, 026705] has previously been applied to reconstruct structures from sparse noncrystalline data of objects with unknown orientations [Philipp et al. (2012 ▶), Opt. Express, 20, 13129-13137; Ayyer et al. (2014 ▶), Opt. Express, 22, 2403-2413]. Here, it is shown that sparse data which cannot be oriented on a per-frame basis can be used effectively as crystallographic data. As a proof-of-principle, reconstruction of the three-dimensional diffraction intensity using sparse data frames from a 1.35 kDa molecule crystal is demonstrated. The results suggest that serial microcrystallography is, in principle, not limited by the fluence of the X-ray source, and collection of complete data sets should be feasible at, for instance, storage-ring X-ray sources.

Indexed as

EMC algorithmreconstruction of diffraction intensitysparse dataX-ray serial microcrystallography

Identifiers

PMID25610625
PMCPMC4285878

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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.