ArticleComputer methods and programs in biomedicine2022
A molecular prior distribution for Bayesian inference based on Wilson statistics.
Article in Computer methods and programs in biomedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Confidence-guided cryo-EM map optimisation with LocScale-2.0.Nature communications · 2026Article
- Subspace Method of Moments forSIAM journal on imaging sciences · 2026Article
- Sensitive detection of structural dynamics using a statistical framework for comparative crystallography.Science advances · 2025Article
- Efficient high-resolution refinement in cryo-EM with stochastic gradient descent.Acta crystallographica. Section D, Structural biology · 2025Article
- Article
- Cryo-EM Heterogeneity Analysis using Regularized Covariance Estimation and Kernel Regression.bioRxiv : the preprint server for biology · 2024Article
- Self Fourier shell correlation: properties and application to cryo-ET.Communications biology · 2024Article
- Self Fourier shell correlation: properties and application to cryo-ET.bioRxiv : the preprint server for biology · 2023Article
- Autocorrelation analysis for cryo-EM with sparsity constraints: Improved sample complexity and projection-based algorithms.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Transformations between rotational and translational invariants formulated in reciprocal spaces.Journal of structural biology: X · 2023Article
- Toward Single Particle Reconstruction without Particle Picking: Breaking the Detection Limit.SIAM journal on imaging sciences · 2023Article
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2 authors.
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Abstract
BACKGROUND AND
objectiveWilson statistics describe well the power spectrum of proteins at high frequencies. Therefore, it has found several applications in structural biology, e.g., it is the basis for sharpening steps used in cryogenic electron microscopy (cryo-EM). A recent paper gave the first rigorous proof of Wilson statistics based on a formalism of Wilson's original argument. This new analysis also leads to statistical estimates of the scattering potential of proteins that reveal a correlation between neighboring Fourier coefficients. Here we exploit these estimates to craft a novel prior that can be used for Bayesian inference of molecular structures.
methodsWe describe the properties of the prior and the computation of its hyperparameters. We then evaluate the prior on two synthetic linear inverse problems, and compare against a popular prior in cryo-EM reconstruction at a range of SNRs.
resultsWe show that the new prior effectively suppresses noise and fills-in low SNR regions in the spectral domain. Furthermore, it improves the resolution of estimates on the problems considered for a wide range of SNR and produces Fourier Shell Correlation curves that are insensitive to masking effects.
conclusionsWe analyze the assumptions in the model, discuss relations to other regularization strategies, and postulate on potential implications for structure determination in cryo-EM.
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