ArticleStructure (London, England : 1993)2025
Automated model-free analysis of cryo-EM volume ensembles with SIREn.
Article in Structure (London, England : 1993), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Heterogeneous reconstruction algorithms for cryoEM achieve limited particle classification accuracy on real benchmark datasets.bioRxiv : the preprint server for biology · 2026Article
- Engineered Cas9 complexes establish an experimentally grounded benchmark for heterogeneous cryoEM reconstruction methods.bioRxiv : the preprint server for biology · 2026Article
- Capturing ribosomal structures in cellular extracts with cryoPRISM: A purification-free cryoEM approach reveals novel structural states.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Resolving structural heterogeneity in situ through cryogenic electron tomography.Current opinion in structural biology · 2026Review
- Rapid structural analysis of bacterial ribosomes in situ.Communications biology · 2025Article
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4 authors.
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Abstract
Cryogenic electron microscopy (cryo-EM) has the potential to capture snapshots of proteins in motion and generate hypotheses linking conformational states to biological function. This potential has been increasingly realized by the advent of machine learning models that allow 100s-1,000s of 3D density maps to be generated from a single dataset. How to identify distinct structural states within these volume ensembles and quantify their relative occupancies remain open questions. Here, we present an approach to inferring variable regions directly from a volume ensemble based on the statistical co-occupancy of voxels, as well as a 3D convolutional neural network that predicts binarization thresholds for volumes in an unbiased and automated manner. We show that these tools recapitulate known heterogeneity in a variety of simulated and real cryo-EM datasets and highlight how integrating these tools with existing data processing pipelines enables improved particle curation.
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