Reconstruction of viruses from solution x-ray scattering data

1995 ◽  
Author(s):  
Yibin Zheng ◽  
Peter C. Doerschuk ◽  
John E. Johnson
Keyword(s):  
Scattering Data ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

scholarly journals Global Small-Angle X-ray Scattering Data Analysis of Triacylglycerols in the Molten State (Part I)

2018 ◽  
Vol 122 (45) ◽  
pp. 10320-10329 ◽  
Author(s):  
Amin Sadeghpour ◽  
Marjorie Ladd Parada ◽  
Josélio Vieira ◽  
Megan Povey ◽  
Michael Rappolt
Keyword(s):  
Data Analysis ◽  
Small Angle ◽  
Scattering Data ◽  
Molten State ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

scholarly journals REGALS: a general method to deconvolve X-ray scattering data from evolving mixtures

2020 ◽  
Author(s):  
Steve P. Meisburger ◽  
Da Xu ◽  
Nozomi Ando
Keyword(s):  
A Priori ◽  
Scattering Data ◽  
Biological Macromolecules ◽  
Time Resolved ◽  
X Ray ◽  
X Ray Scattering ◽  
Open Source Software Package ◽  
Saxs Analysis ◽  
Structural Methods ◽  
Ray Scattering

AbstractMixtures of biological macromolecules are inherently difficult to study using structural methods, as increasing complexity presents new challenges for data analysis. Recently, there has been growing interest in studying evolving mixtures using small-angle X-ray scattering (SAXS) in conjunction with time-resolved, high-throughput, or chromatography-coupled setups. Deconvolution and interpretation of the resulting datasets, however, are nontrivial when neither the scattering components nor the way in which they evolve are known a priori. To address this issue, we introduce the REGALS method (REGularized Alternating Least Squares), which incorporates simple expectations about the data as prior knowledge and utilizes parameterization and regularization to provide robust deconvolution solutions. The restraints used by REGALS are general properties such as smoothness of profiles and maximum dimensions of species, which makes it well-suited for exploring datasets with unknown species. Here we apply REGALS to analyze experimental data from four types of SAXS experiment: anion-exchange (AEX) coupled SAXS, ligand titration, time-resolved mixing, and time-resolved temperature jump. Based on its performance with these challenging datasets, we anticipate that REGALS will be a valuable addition to the SAXS analysis toolkit and enable new experiments. The software is implemented in both MATLAB and python and is available freely as an open-source software package.

scholarly journals Lipid Bilayer Structure Determined by the Simultaneous Analysis of Neutron and X-Ray Scattering Data

2008 ◽  
Vol 95 (5) ◽  
pp. 2356-2367 ◽  
Author(s):  
Norbert Kučerka ◽  
John F. Nagle ◽  
Jonathan N. Sachs ◽  
Scott E. Feller ◽  
Jeremy Pencer ◽  
...  
Keyword(s):  
Lipid Bilayer ◽  
Simultaneous Analysis ◽  
Scattering Data ◽  
Bilayer Structure ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

scholarly journals Exploiting the full quantum crystallography

2018 ◽  
Vol 96 (7) ◽  
pp. 599-605 ◽  
Author(s):  
Lou Massa ◽  
Chérif F. Matta
Keyword(s):  
Quantum Mechanics ◽  
Electron Density ◽  
Mathematical Structure ◽  
Scattering Data ◽  
X Ray ◽  
X Ray Crystallography ◽  
X Ray Scattering ◽  
Fundamental Value ◽  
Quantum Crystallography ◽  
Ray Scattering

Quantum crystallography (QCr) is a branch of crystallography aimed at obtaining the complete quantum mechanics of a crystal given its X-ray scattering data. The fundamental value of obtaining an electron density matrix that is N-representable is that it ensures consistency with an underlying properly antisymmetrized wavefunction, a requirement of quantum mechanical validity. However, X-ray crystallography has progressed in an impressive way for decades based only upon the electron density obtained from the X-ray scattering data without the imposition of the mathematical structure of quantum mechanics. Therefore, one may perhaps ask regarding N-representability “why bother?” It is the purpose of this article to answer such a question by succinctly describing the advantage that is opened by QCr.

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