Evidence map›Paper›PMID 36641207›Full record

ArticleMethods in enzymology2023

Reconstruction of 3D density from solution scattering.

Thomas D Grant

Abstract read
In one paragraph

Article in Methods in enzymology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Temporal ghost imaging for pump-probe X-ray solution scattering.Acta crystallographica. Section A, Foundations and advances · 2025
    Article
  5. Crystal structure of coagulation factor XII N-terminal domains 1-5.Acta crystallographica. Section D, Structural biology · 2025
    Article
  6. Review
  7. Review
  8. Structural insights into redox signal transduction mechanisms in the control of nitrogen fixation by the NifLA system.Proceedings of the National Academy of Sciences of the United States of America · 2023
    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

1 author.

Thomas D GrantDepartment of Structural Biology, Jacobs School of Medicine and Biomedical Sciences, SUNY University at Buffalo, Buffalo, NY, United States. Electronic address: tdgrant@buffalo.edu.

Funding

High-resolution molecular recognition of ligands using solution X-ray scatteringR01GM133998 · NIGMS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI GRANT, THOMAS D. · 2019 to 2022
$1.3M
NIGMS NIH HHS R01 GM133998
6 · The paper itself

Abstract

Ab initio modeling methods have proven to be powerful means of interpreting solution scattering data. In the absence of atomic models, or complementary to them, ab initio modeling approaches can be used for generating low-resolution particle envelopes using only solution scattering profiles. Recently, a new ab initio reconstruction algorithm has been introduced to the scientific community, called DENSS. DENSS is unique among ab initio modeling algorithms in that it solves the inverse scattering problem, i.e., the 1D scattering intensities are directly used to determine the 3D particle density. The reconstruction of particle density has several advantages over conventional uniform density modeling approaches, including the ability to reconstruct a much wider range of particle types and the ability to visualize low-resolution density fluctuations inside the particle envelope. In this chapter we will discuss the theory behind this new approach, how to use DENSS, and how to interpret the results. Several examples with experimental and simulated data will be provided.

Indexed as

AlgorithmsScattering, Small AngleAb initioDensityImagingModelingPhase retrievalSmall angle scattering

Identifiers

PMID36641207
PMCPMC10246859

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.