Evidence map›Paper›PMID 37645688›Full record

ArticleBiological imaging2023

Fast principal component analysis for cryo-electron microscopy images.

Nicholas F Marshall, Oscar Mickelin, Yunpeng Shi, Amit Singer

Abstract 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. 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. AlignPCA-2D: PCA-reduced Euclidean vector alignment for 2D classification in cryo-EM.Acta crystallographica. Section D, Structural biology · 2026
    Article
  4. Subspace Method of Moments forSIAM journal on imaging sciences · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Autocorrelation analysis for cryo-EM with sparsity constraints: Improved sample complexity and projection-based algorithms.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

4 authors.

Nicholas F MarshallDepartment of Mathematics, Oregon State University, Corvallis, Oregon 97331, USA.
Oscar MickelinProgram in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08544, USA.ORCID 0000-0003-0167-1992
Yunpeng ShiProgram in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08544, USA.ORCID 0000-0003-2388-2766
Amit SingerProgram in Applied and Computational Mathematics, Princeton University, Princeton, New Jersey 08544, USA.

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

Principal component analysis (PCA) plays an important role in the analysis of cryo-electron microscopy (cryo-EM) images for various tasks such as classification, denoising, compression, and ab initio modeling. We introduce a fast method for estimating a compressed representation of the 2-D covariance matrix of noisy cryo-EM projection images affected by radial point spread functions that enables fast PCA computation. Our method is based on a new algorithm for expanding images in the Fourier-Bessel basis (the harmonics on the disk), which provides a convenient way to handle the effect of the contrast transfer functions. For

Indexed as

Covariance estimationcryo-EMdenoisingFourier–Besselprincipal component analysissingle particle reconstruction

Identifiers

PMID37645688
PMCPMC10465116

What OpenQuestion holds

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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.