ArticleStructure (London, England : 1993)2020
High-Throughput Cryo-EM Enabled by User-Free Preprocessing Routines.
Article in Structure (London, England : 1993), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- An unattended image-processing pipeline for on-the-fly quality assessment and 3D exploration in cryo-EM.Acta crystallographica. Section D, Structural biology · 2026Article
- prismPYP: Power-spectrum and image domain learning for self-supervised micrograph evaluation.Structure (London, England : 1993) · 2026Article
- A comprehensive foundation model for cryo-EM image processing.Nature methods · 2026Article
- Combining Cryo-EM with Computational Approaches To Revolutionize Structural Biology.The protein journal · 2025Review
- CryoSift: an accessible and automated CNN-driven tool for cryo-EM 2D class selection.Acta crystallographica. Section F, Structural biology communications · 2025Article
- Magellon - an extensible platform for cryo-EM data visualization, management and processing.IUCrJ · 2025Article
- Few-Shot Classification of Cryo-EM Micrographs Using Triplet Loss Embeddings.bioRxiv : the preprint server for biology · 2025Article
- Rapid structural analysis of bacterial ribosomes in situ.Communications biology · 2025Article
- Miffi: Improving the accuracy of CNN-based cryo-EM micrograph filtering with fine-tuning and Fourier space information.Journal of structural biology · 2024Article
- Rapid structural analysis of bacterial ribosomesbioRxiv : the preprint server for biology · 2024Article
- Miffi: Improving the accuracy of CNN-based cryo-EM micrograph filtering with fine-tuning and Fourier space information.bioRxiv : the preprint server for biology · 2024Article
- Structure of mechanically activated ion channel OSCA2.3 reveals mobile elements in the transmembrane domain.Structure (London, England : 1993) · 2024Article
- Scaling up cryo-EM for biology and chemistry: The journey from niche technology to mainstream method.Structure (London, England : 1993) · 2023Review
- Mass spectrometers as cryoEM grid preparation instruments.Current opinion in structural biology · 2023Review
- Tethered agonist activated ADGRF1 structure and signalling analysis reveal basis for G protein coupling.Nature communications · 2023Article
- Multiple-image super-resolution of cryo-electron micrographs based on deep internal learning.Biological imaging · 2023Article
- Article
- MOLASS: Software for automatic processing of matrix data obtained from small-angle X-ray scattering and UV-visible spectroscopy combined with size-exclusion chromatography.Biophysics and physicobiology · 2023Article
- Emerging Themes in CryoEM─Single Particle Analysis Image Processing.Chemical reviews · 2022Review
- Evolving Experimental Techniques for Structure-Based Drug Design.The journal of physical chemistry. B · 2022Review
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4 authors.
Funding
Abstract
Single-particle cryoelectron microscopy (cryo-EM) continues to grow into a mainstream structural biology technique. Recent developments in data collection strategies alongside new sample preparation devices herald a future where users will collect multiple datasets per microscope session. To make cryo-EM data processing more automatic and user-friendly, we have developed an automatic pipeline for cryo-EM data preprocessing and assessment using a combination of deep-learning and image-analysis tools. We have verified the performance of this pipeline on a number of datasets and extended its scope to include sample screening by the user-free assessment of the qualities of a series of datasets under different conditions. We propose that our workflow provides a decision-free solution for cryo-EM, making data preprocessing more generalized and robust in the high-throughput era as well as more convenient for users from a range of backgrounds.
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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.