ArticleJournal of structural biology2010
Subtomogram alignment by adaptive Fourier coefficient thresholding.
Article in Journal of structural biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- DUAL: deep unsupervised simultaneous simulation and denoising for cryo-electron tomography.bioRxiv : the preprint server for biology · 2024Article
- End-to-end robust joint unsupervised image alignment and clustering.Proceedings. IEEE International Conference on Computer Vision · 2021Article
- Gum-Net: Unsupervised Geometric Matching for Fast and Accurate 3D Subtomogram Image Alignment and Averaging.Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition · 2020Article
- Fine-grained alignment of cryo-electron subtomograms based on MPI parallel optimization.BMC bioinformatics · 2019Article
- An integration of fast alignment and maximum-likelihood methods for electron subtomogram averaging and classification.Bioinformatics (Oxford, England) · 2018Article
- The advent of structural biologyBiophysics reports · 2017Article
- Alignment algorithms and per-particle CTF correction for single particle cryo-electron tomography.Journal of structural biology · 2016Article
- Practical workflow for cryo focused-ion-beam milling of tissues and cells for cryo-TEM tomography.Journal of structural biology · 2014Article
- Conformational States of macromolecular assemblies explored by integrative structure calculation.Structure (London, England : 1993) · 2013Article
- Automated target segmentation and real space fast alignment methods for high-throughput classification and averaging of crowded cryo-electron subtomograms.Bioinformatics (Oxford, England) · 2013Article
- High-throughput subtomogram alignment and classification by Fourier space constrained fast volumetric matching.Journal of structural biology · 2012Article
- High precision alignment of cryo-electron subtomograms through gradient-based parallel optimization.BMC systems biology · 2012Article
- New insights into HTLV-1 particle structure, assembly, and Gag-Gag interactions in living cells.Viruses · 2011Review
- Gradient-based high precision alignment of cryo-electron subtomograms.IEEE International Conference on Systems Biology : [proceedings]. IEEE International Conference on Systems Biology · 2011Article
- Analysis of the intact surface layer of Caulobacter crescentus by cryo-electron tomography.Journal of bacteriology · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
In the past few years, three-dimensional (3D) subtomogram alignment has become an important tool in cryo-electron tomography (CET). This technique allows one to produce higher resolution images of structures which can not be reconstructed using single-particle methods. Building on previous work, we present a new dissimilarity measure between subtomograms that works well for the noisy images that often occur in CET images. A technique that is more robust to noise provides the ability to analyze macromolecules in thicker samples such as whole cells or lower the defocus in thinner samples to push the first zero of the Contrast Transfer Function (CTF). Our method, Threshold Constrained Cross-Correlation (TCCC), uses statistics of the noise to automatically select only a small percentage of the Fourier coefficients to compute the cross-correlation, which has two main advantages: first, it reduces the influence of the noise by looking at only those peaks dominated by signal; and second, it avoids the missing wedge normalization problem since we consider the same number of coefficients for all possible pairs of subtomograms. We present results with synthetic and real data to compare our approach with other existing methods under different SNR and missing wedge conditions, and show that TCCC improves alignment results for datasets with SNR<0.1. We have made our source code freely available for the community.
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.