Atomic-Level Insights from SWAXS: Quantifying Uncertainty in Biological Models
Patrick K. Oduro, Jitendra Singh, Sarah Chamberlain, Thomas D. Grant

TL;DR
This paper introduces a new method using Shannon information theory to evaluate the precision and accuracy of SWAXS data and models, improving confidence in structural biology results.
Contribution
A novel statistical framework for assessing SWAXS data precision and model accuracy using Shannon information theory.
Findings
The method provides objective metrics for comparing SWAXS datasets and evaluating model-data fit.
Per-atom coordinate uncertainty estimates identify the most reliably determined regions of structural models.
Validation shows the metrics are robust and provide meaningful assessments of SWAXS models.
Abstract
Small- and wide-angle X-ray scattering (SWAXS) is a powerful technique for investigating the shape and dynamics of biological macromolecules in solution. Despite its growing popularity, the field has lacked standardized criteria for evaluating data precision and model accuracy, undermining confidence in results and limiting wider adoption. To address this critical gap, we introduce a suite of objective assessment metrics based on Shannon information theory that quantitatively evaluate both data precision and model-data agreement. Our approach provides three key advances: (1) accurate quantification of the amount and precision of information in a SWAXS profile that enables objective comparison between datasets; (2) a data quality-aware measure of model-data fit that provides more trustworthy structural assessments; and (3) a novel statistical framework that leverages conformational…
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Taxonomy
TopicsLiterature and Culture Studies · Historical and Political Studies · French Historical and Cultural Studies
