ArticleNature methods2023
OPUS-DSD: deep structural disentanglement for cryo-EM single-particle analysis.
Article in Nature methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Engineered Cas9 complexes establish an experimentally grounded benchmark for heterogeneous cryoEM reconstruction methods.bioRxiv : the preprint server for biology · 2026Article
- Bayesian perspective for orientation determination in cryo-EM with application to structural heterogeneity analysis.Acta crystallographica. Section D, Structural biology · 2026Article
- Integrated experimental and AI innovations for RNA structure determination.Nature biotechnology · 2026Review
- A comprehensive foundation model for cryo-EM image processing.Nature methods · 2026Article
- Reaching the full potential of cryo-EM reconstructions with molecular dynamics simulations at 310 K: Actin filaments as an example.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Bayesian Perspective for Orientation Determination in Cryo-EM with Application to Structural Heterogeneity Analysis.bioRxiv : the preprint server for biology · 2025Article
- Merging conformational landscapes in a single consensus space with FlexConsensus algorithm.Nature methods · 2025Article
- CryoDRGN-AI: neural ab initio reconstruction of challenging cryo-EM and cryo-ET datasets.Nature methods · 2025Article
- Real-space heterogeneous reconstruction, refinement, and disentanglement of CryoEM conformational states with HetSIREN.Nature communications · 2025Article
- Conformational landscapes of a class I ribonucleotide reductase complex during turnover reveal intrinsic dynamics and asymmetry.Nature communications · 2025Article
- Article
- Learning structural heterogeneity from cryo-electron sub-tomograms with tomoDRGN.Nature methods · 2024Article
- Structure-based investigation of a DNA aptamer targeting PTK7 reveals an intricate 3D fold guiding functional optimization.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- OPUS-DSD: deep structural disentanglement for cryo-EM single-particle analysis.Nature methods · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cryo-electron microscopy (cryo-EM) captures snapshots of dynamic macromolecules, collectively illustrating the involved structural landscapes. This provides an exciting opportunity to explore the structural variations of macromolecules under study. However, traditional cryo-EM single-particle analysis often yields static structures. Here we describe OPUS-DSD, an algorithm capable of efficiently reconstructing the structural landscape embedded in cryo-EM data. OPUS-DSD uses a three-dimensional convolutional encoder-decoder architecture trained with cryo-EM images, thereby encoding structural variations into a smooth and easily analyzable low-dimension space. This space can be traversed to reconstruct continuous dynamics or clustered to identify distinct conformations. OPUS-DSD can offer meaningful insights into the structural variations of macromolecules, filling in the gaps left by traditional cryo-EM structural determination, and potentially improves the reconstruction resolution by reliably clustering similar particles within the dataset. These functionalities are especially relevant to the study of highly dynamic biological systems. OPUS-DSD is available at https://github.com/alncat/opusDSD .
Indexed as
Identifiers
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.