ArticlePhysical review. E, Statistical, nonlinear, and soft matter physics2013
Model-independent decomposition of two-state data.
Article in Physical review. E, Statistical, nonlinear, and soft matter physics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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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.
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Who cites it
1 citing paper in PubMed.
- Conformational Mobility in Cytochrome P450 3A4 Explored by Pressure-Perturbation EPR Spectroscopy.Biophysical journal · 2016Article
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2 authors.
Funding
Abstract
Two-state models often provide a reasonable approximation of protein behaviors such as partner binding, folding, and conformational changes. Many different techniques have been developed to determine the population ratio between two states as a function of different experimental conditions. Data analysis is accomplished either by fitting individual measured spectra to a linear combination of known basis spectra or alternatively by decomposing the entire set of spectra into two components using a least-squares optimization of free parameters within an assumed population model. Here we demonstrate that it is possible to determine the population ratio in a two-state system directly from data without an a priori model for basis spectra or populations by applying physical constraints iteratively to a singular value decomposition of optical fluorescence, x-ray-scattering, and electron paramagnetic resonance data.
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