ArticleNature methods2025
A realistic phantom dataset for benchmarking cryo-ET data annotation.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Graph identification of proteins in tomograms (GRIP-Tomo) 2.0: Topologically aware classification for proteins.Protein science : a publication of the Protein Society · 2026Article
- Lessons learned from a Kaggle challenge for particle picking in cryo-electron tomography.Nature methods · 2026Article
- Bridging annotated microscopy imaging data and analysis method development for scientific discovery.Patterns (New York, N.Y.) · 2026Review
- AreTomoLive: automated reconstruction of comprehensively corrected and denoised cryo-electron tomograms in real time and at high throughput.Nature methods · 2026Article
- Characterization Standard forbioRxiv : the preprint server for biology · 2026Article
- Evaluating the Volta phase plate for improved tomogram alignment in cryo-electron tomography.IUCrJ · 2026Article
- copick: An open dataset interface and toolkit for collaborative annotation and analysis of cryo-electron tomography data.Protein science : a publication of the Protein Society · 2026Article
- A robust workflow for 3D imaging of human mitochondria using cryo-electron tomography.bioRxiv : the preprint server for biology · 2026Article
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Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cryo-electron tomography (cryo-ET) is a powerful technique for imaging molecular complexes in their native cellular environments. However, identifying the vast majority of molecular species in cellular tomograms remains prohibitively difficult. Machine learning (ML) methods provide an opportunity to automate the annotation process, but algorithm development has been hindered by the lack of large, standardized datasets. Here we present an experimental phantom dataset with comprehensive ground-truth annotations for six molecular species to spur new algorithm development and benchmark existing tools. This annotated dataset is available on the CryoET Data Portal with infrastructure to streamline access for methods developers across fields.
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