ArticleStructure (London, England : 1993)2022
Compressed sensing for electron cryotomography and high-resolution subtomogram averaging of biological specimens.
Article in Structure (London, England : 1993), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
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Who cites it
6 citing papers in PubMed, 15 citations in OpenAlex.
- A variational framework with composite sparse regularization for cryo-electron tomography reconstruction.Bioinformatics (Oxford, England) · 2026Article
- CryoSamba: Self-supervised deep volumetric denoising for cryo-electron tomography data.Journal of structural biology · 2025Article
- An image processing pipeline for electron cryo-tomography in RELION-5.FEBS open bio · 2024Article
- A deep learning method for simultaneous denoising and missing wedge reconstruction in cryogenic electron tomography.Nature communications · 2024Article
- Charting the molecular landscape of the cell.Structure (London, England : 1993) · 2023Review
- A method for restoring signals and revealing individual macromolecule states in cryo-ET, REST.Nature communications · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
Cryoelectron tomography (cryo-ET) and subtomogram averaging (STA) allow direct visualization and structural studies of biological macromolecules in their native cellular environment, in situ. Often, low signal-to-noise ratios in tomograms, low particle abundance within the cell, and low throughput in typical cryo-ET workflows severely limit the obtainable structural information. To help mitigate these limitations, here we apply a compressed sensing approach using 3D second-order total variation (CS-TV
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Registered trials
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.