ArticleNature communications2021
FSC-Q: a CryoEM map-to-atomic model quality validation based on the local Fourier shell correlation.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed.
- Structural analysis of uridine modifications in solved RNA structures.NAR genomics and bioinformatics · 2026Article
- An Empirical Biasing Force Constant to Minimize Overfitting in Cryo-EM Flexible Fitting Refinement.Journal of chemical information and modeling · 2025Article
- Q-score as a reliability measure for protein, nucleic acid and small-molecule atomic coordinate models derived from 3DEM maps.Acta crystallographica. Section D, Structural biology · 2025Article
- Structural determinants of rotavirus proteolytic activation.PLoS pathogens · 2025Article
- Structural mechanism for the recognition of E2F1 by the ubiquitin ligase adaptor Cyclin F.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- AI-based quality assessment methods for protein structure models from cryo-EM.Current research in structural biology · 2025Review
- Advances in cryo-electron microscopy (cryoEM) for structure-based drug discovery.Expert opinion on drug discovery · 2025Review
- Connecting the dots: deep learning-based automated model building methods in cryo-EM.Frontiers in molecular biosciences · 2025Review
- A Visual Environment for Data Driven Protein Modeling and Validation.IEEE transactions on visualization and computer graphics · 2024Article
- Bacterial selenocysteine synthase structure revealed by single-particle cryoEM.Current research in structural biology · 2024Article
- Automated simulation-based membrane protein refinement into cryo-EM data.Biophysical journal · 2023Article
- Residue-level error detection in cryoelectron microscopy models.Structure (London, England : 1993) · 2023Article
- Integrating Molecular Models Into CryoEM Heterogeneity Analysis Using Scalable High-resolution Deep Gaussian Mixture Models.Journal of molecular biology · 2023Article
- Development and validation of a newly developed nomogram for predicting the risk of deep vein thrombosis after surgery for lower limb fractures in elderly patients.Frontiers in surgery · 2023Article
- Using deep-learning predictions of inter-residue distances for model validation.Acta crystallographica. Section D, Structural biology · 2022Article
- Overview and applications of map and model validation tools in the CCP-EM software suite.Faraday discussions · 2022Review
- Juxtaposition of Bub1 and Cdc20 on phosphorylated Mad1 during catalytic mitotic checkpoint complex assembly.Nature communications · 2022Article
- Article
- EMDA: A Python package for Electron Microscopy Data Analysis.Journal of structural biology · 2022Article
- Atomic model validation using the CCP-EM software suite.Acta crystallographica. Section D, Structural biology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, advances in cryoEM have dramatically increased the resolution of reconstructions and, with it, the number of solved atomic models. It is widely accepted that the quality of cryoEM maps varies locally; therefore, the evaluation of the maps-derived structural models must be done locally as well. In this article, a method for the local analysis of the map-to-model fit is presented. The algorithm uses a comparison of two local resolution maps. The first is the local FSC (Fourier shell correlation) between the full map and the model, while the second is calculated between the half maps normally used in typical single particle analysis workflows. We call the quality measure "FSC-Q", and it is a quantitative estimation of how much of the model is supported by the signal content of the map. Furthermore, we show that FSC-Q may be helpful to detect overfitting. It can be used to complement other methods, such as the Q-score method that estimates the resolvability of atoms.
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.