ReviewChemical reviews2022
Emerging Themes in CryoEM─Single Particle Analysis Image Processing.
Review in Chemical reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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
24 citing papers in PubMed, 45 citations in OpenAlex.
- Higher-order structural organization of mitochondrial metabolism.The Journal of biological chemistry · 2026Review
- EMReady2: improvement of cryo-EM and cryo-ET maps by local quality-aware deep learning with Mamba.Nature communications · 2026Article
- CryoFSL: an annotation-efficient, few-shot learning framework for robust protein particle picking in cryo-electron microscopy micrographs.Briefings in bioinformatics · 2026Article
- CryoSIP: unleashing protein high-resolution Cryo-EM via semantic-instance collaborative picking.Briefings in bioinformatics · 2026Article
- Cytochrome nanowires under electron microscopy.Emerging topics in life sciences · 2026Review
- EMProt improves structure determination from cryo-EM maps.Nature structural & molecular biology · 2026Article
- Nanopore Trap for Label-Free Fingerprinting of Surface-modified Single Nanoparticles.Small methods · 2026Article
- Isolation and Visualization Fusobacterium nucleatum Microcompartments.Methods in molecular biology (Clifton, N.J.) · 2026Article
- CryoSift: an accessible and automated CNN-driven tool for cryo-EM 2D class selection.Acta crystallographica. Section F, Structural biology communications · 2025Article
- Article
- CryoFSL: An Annotation-Efficient, Few-Shot Learning Framework for Robust Protein Particle Picking in Cryo-EM Micrographs.bioRxiv : the preprint server for biology · 2025Article
- RNA sample optimization for cryo-EM analysis.Nature protocols · 2025Review
- Self-supervised machine learning framework for high-throughput electron microscopy.Science advances · 2025Article
- ModeHunter: A Package for the Reductionist Analysis, Animation, and Application of Elastic Biomolecular Motion.The journal of physical chemistry. B · 2025Article
- Unravelling complex mechanisms in materials processes with cryogenic electron microscopy.Chemical science · 2025Review
- Comparative Analysis of Symmetry Parameters in the E2 Inner Core of the Pyruvate Dehydrogenase Complex.International journal of molecular sciences · 2024Article
- UPicker: a semi-supervised particle picking transformer method for cryo-EM micrographs.Briefings in bioinformatics · 2024Article
- MDFF_NM: Improved Molecular Dynamics Flexible Fitting into Cryo-EM Density Maps with a Multireplica Normal Mode-Based Search.Journal of chemical information and modeling · 2024Article
- A Data Set of Paired Structural Segments Between Protein Data Bank and AlphaFold DB for Medium-Resolution Cryo-EM Density Maps: A Gap in Overall Structural Quality.Bioinformatics research and applications : ... international symposium, ISBRA ... proceedings. ISBRA (Conference) · 2024Article
- Cryo-electron microscopy-based drug design.Frontiers in molecular biosciences · 2024Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars have contributed to the boosting of CryoEM in the past decade. This work reviews the main contributions in image processing to the current reconstruction workflow of single particle analysis (SPA) by CryoEM. Our review emphasizes the time evolution of the algorithms across the different steps of the workflow differentiating between two groups of approaches: analytical methods and deep learning algorithms. We present an analysis of the current state of the art. Finally, we discuss the emerging problems and challenges still to be addressed in the evolution of CryoEM image processing methods in SPA.
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What OpenQuestion holds
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.