Evidence map›Paper›PMID 38516630›Full record

ArticleBiological imaging2024

Moment-based metrics for molecules computable from cryogenic electron microscopy images.

Andy Zhang, Oscar Mickelin, Joe Kileel, Eric J Verbeke, Nicholas F Marshall, Marc Aurèle Gilles, Amit Singer

Abstract read
In one paragraph

Article in Biological imaging, 2024. 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. Subspace Method of Moments forSIAM journal on imaging sciences · 2026
    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

7 authors.

Andy ZhangProgram in Applied and Computational Mathematics, Princeton University, Princeton, NJ, USA.ORCID https://orcid.org/0009-0006-0420-044X
Oscar MickelinProgram in Applied and Computational Mathematics, Princeton University, Princeton, NJ, USA.ORCID https://orcid.org/0000-0003-0167-1992
Joe KileelDepartment of Mathematics and Oden Institute, University of Texas at Austin, Austin, TX, USA.ORCID https://orcid.org/0000-0001-9926-9170
Eric J VerbekeProgram in Applied and Computational Mathematics, Princeton University, Princeton, NJ, USA.ORCID https://orcid.org/0000-0001-9506-424X
Nicholas F MarshallDepartment of Mathematics, Oregon State University, Corvallis, OR, USA.ORCID https://orcid.org/0000-0002-1871-6862
Marc Aurèle GillesProgram in Applied and Computational Mathematics, Princeton University, Princeton, NJ, USA.ORCID https://orcid.org/0000-0002-0548-6834
Amit SingerProgram in Applied and Computational Mathematics, Princeton University, Princeton, NJ, USA.ORCID https://orcid.org/0000-0002-6975-7955

Funding

Reconstruction of heterogeneous and small macromolecules by cyro-EMR01GM136780 · NIGMS · PRINCETON UNIVERSITY · PI SINGER, AMIT · 2020 to 2023
$1.3M
NIGMS NIH HHS R01 GM136780
6 · The paper itself

Abstract

Single-particle cryogenic electron microscopy (cryo-EM) is an imaging technique capable of recovering the high-resolution three-dimensional (3D) structure of biological macromolecules from many noisy and randomly oriented projection images. One notable approach to 3D reconstruction, known as Kam's method, relies on the moments of the two-dimensional (2D) images. Inspired by Kam's method, we introduce a rotationally invariant metric between two molecular structures, which does not require 3D alignment. Further, we introduce a metric between a stack of projection images and a molecular structure, which is invariant to rotations and reflections and does not require performing 3D reconstruction. Additionally, the latter metric does not assume a uniform distribution of viewing angles. We demonstrate the uses of the new metrics on synthetic and experimental datasets, highlighting their ability to measure structural similarity.

Indexed as

alignment-free metricKam’s methodmethod of momentsprotein structural similarityrotationally invariant distancestructural search

Identifiers

PMID38516630
PMCPMC10951804

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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.