SAS-cam: a program for automatic processing and analysis of small-angle scattering data

2020 ◽  
Vol 53 (4) ◽  
pp. 1147-1153 ◽  
Author(s):  
Hongjin Wu ◽  
Yiwen Li ◽  
Guangfeng Liu ◽  
Haiguang Liu ◽  
Na Li
Keyword(s):  
Data Analysis ◽  
High Throughput ◽  
Small Angle ◽  
Scattering Data ◽  
Model Parameters ◽  
Biological Macromolecules ◽  
Shanghai Synchrotron Radiation Facility ◽  
Saxs Data ◽  
Model Interpretation ◽  
Analysis Process

Small-angle X-ray scattering (SAXS) is a widely used method for investigating biological macromolecules in structural biology, providing information on macromolecular structures and dynamics in solution. Modern synchrotron SAXS beamlines are characterized as high-throughput, capable of collecting large volumes of data and thus demanding fast data processing for efficient beamline operations. This article presents a fully automated and high-throughput SAXS data analysis pipeline, SAS-cam, primarily based on the SASTBX package. Five modules are included in SAS-cam, encompassing the data analysis process from data reduction to model interpretation. The model parameters are extracted from SAXS profiles and stored in an HTML summary file, ready for online visualization using a web browser. SAS-cam can provide the user with the possibility of optimizing experimental parameters based on real-time feedback and it therefore significantly improves the efficiency of beam time. SAS-cam is installed on the BioSAXS beamline at the Shanghai Synchrotron Radiation Facility. The source code is available upon request.

scholarly journals SASfit: a tool for small-angle scattering data analysis using a library of analytical expressions

2015 ◽  
Vol 48 (5) ◽  
pp. 1587-1598 ◽  
Author(s):  
Ingo Breßler ◽  
Joachim Kohlbrecher ◽  
Andreas F. Thünemann
Keyword(s):  
Data Analysis ◽  
Reference Material ◽  
Small Angle ◽  
Fractal Model ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Model Parameters ◽  
Angle Scattering ◽  
Confidence Assessment ◽  
Analysis Workflow

SASfitis one of the mature programs for small-angle scattering data analysis and has been available for many years. This article describes the basic data processing and analysis workflow along with recent developments in theSASfitprogram package (version 0.94.6). They include (i) advanced algorithms for reduction of oversampled data sets, (ii) improved confidence assessment in the optimized model parameters and (iii) a flexible plug-in system for custom user-provided models. A scattering function of a mass fractal model of branched polymers in solution is provided as an example for implementing a plug-in. The newSASfitrelease is available for major platforms such as Windows, Linux and MacOS. To facilitate usage, it includes comprehensive indexed documentation as well as a web-based wiki for peer collaboration and online videos demonstrating basic usage. The use ofSASfitis illustrated by interpretation of the small-angle X-ray scattering curves of monomodal gold nanoparticles (NIST reference material 8011) and bimodal silica nanoparticles (EU reference material ERM-FD-102).

scholarly journals ATSAS2.1, a program package for small-angle scattering data analysis

2006 ◽  
Vol 39 (2) ◽  
pp. 277-286 ◽  
Author(s):  
Petr V. Konarev ◽  
Maxim V. Petoukhov ◽  
Vladimir V. Volkov ◽  
Dmitri I. Svergun
Keyword(s):  
Data Analysis ◽  
Small Angle ◽  
Three Dimensional ◽  
Program Package ◽  
Scattering Data ◽  
Primary Data ◽  
Biological Macromolecules ◽  
Colloidal Solutions ◽  
Angle Scattering ◽  
Recent Developments

The program packageATSAS2.1 for small-angle X-ray and neutron scattering data analysis is presented. The programs included in the package cover the major processing and interpretation steps from primary data reduction to three-dimensional modelling. This system is primarily oriented towards the analysis of biological macromolecules, but could also be used for non-biological isotropic and partially ordered objects (nanoparticle systems, colloidal solutions, polymers in solution and bulk). Recent developments in the programs included inATSAS2.1 are highlighted. The main programs run on multiple hardware platforms, including Windows PC, Linux RedHat and Suse, DEC Alpha, SGI IRIX and Mac OSX.

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 The new NCPSS BL19U2 beamline at the SSRF for small-angle X-ray scattering from biological macromolecules in solution

2016 ◽  
Vol 49 (5) ◽  
pp. 1428-1432 ◽  
Author(s):  
Na Li ◽  
Xiuhong Li ◽  
Yuzhu Wang ◽  
Guangfeng Liu ◽  
Ping Zhou ◽  
...  
Keyword(s):  
Data Processing ◽  
Small Angle ◽  
Dynamic Range ◽  
Silicon Crystal ◽  
High Dynamic Range ◽  
Biological Macromolecules ◽  
Shanghai Synchrotron Radiation Facility ◽  
X Ray ◽  
X Ray Scattering ◽  
Ray Scattering

The beamline BL19U2 is located in the Shanghai Synchrotron Radiation Facility (SSRF) and is its first beamline dedicated to biological material small-angle X-ray scattering (BioSAXS). The electrons come from an undulator which can provide high brilliance for the BL19U2 end stations. A double flat silicon crystal (111) monochromator is used in BL19U2, with a tunable monochromatic photon energy ranging from 7 to 15 keV. To meet the rapidly growing demands of crystallographers, biochemists and structural biologists, the BioSAXS beamline allows manual and automatic sample loading/unloading. A Pilatus 1M detector (Dectris) is employed for data collection, characterized by a high dynamic range and a short readout time. The highly automated data processing pipeline SASFLOW was integrated into BL19U2, with help from the BioSAXS group of the European Molecular Biology Laboratory (EMBL, Hamburg), which provides a user-friendly interface for data processing. The BL19U2 beamline was officially opened to users in March 2015. To date, feedback from users has been positive and the number of experimental proposals at BL19U2 is increasing. A description of the new BioSAXS beamline and the setup characteristics is given, together with examples of data obtained.

High-Throughput Data Analysis of Proteomic Mass Spectra on the SwissBioGrid

2011 ◽  
pp. 228-244
Author(s):  
Andreas Quandt ◽  
Sergio Maffioletti ◽  
Cesare Pautasso ◽  
Heinz Stockinger ◽  
Frederique Lisacek
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
High Throughput ◽  
Protein Function ◽  
Mass Spectra ◽  
High Throughput Data ◽  
Analysis Process ◽  
Speed Up ◽  
Grid Infrastructures ◽  
High Throughput Data Analysis

Proteomics is currently one of the most promising fields in bioinformatics as it provides important insights into the protein function of organisms. Mass spectrometry is one of the techniques to study the proteome, and several software tools exist for this purpose. The authors provide an extendable software platform called swissPIT that combines different existing tools and exploits Grid infrastructures to speed up the data analysis process for the proteomics pipeline.

scholarly journals Small Angle Scattering Data Analysis Assisted by Machine Learning Methods

MRS Advances ◽  
2020 ◽  
Vol 5 (29-30) ◽  
pp. 1577-1584
Author(s):  
Changwoo Do ◽  
Wei-Ren Chen ◽  
Sangkeun Lee
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Small Angle ◽  
Confusion Matrix ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Search Spaces ◽  
Angle Scattering ◽  
Analysis Workflow ◽  
The Right

ABSTRACTSmall angle scattering (SAS) is a widely used technique for characterizing structures of wide ranges of materials. For such wide ranges of applications of SAS, there exist a large number of ways to model the scattering data. While such analysis models are often available from various suites of SAS data analysis software packages, selecting the right model to start with poses a big challenge for beginners to SAS data analysis. Here, we present machine learning (ML) methods that can assist users by suggesting scattering models for data analysis. A series of one-dimensional scattering curves have been generated by using different models to train the algorithms. The performance of the ML method is studied for various types of ML algorithms, resolution of the dataset, and the number of the dataset. The degree of similarities among selected scattering models is presented in terms of the confusion matrix. The scattering model suggestions with prediction scores provide a list of scattering models that are likely to succeed. Therefore, if implemented with extensive libraries of scattering models, this method can speed up the data analysis workflow by reducing search spaces for appropriate scattering models.

Small-angle scattering data analysis for dense polydisperse systems: the FLAC program

2000 ◽  
Vol 133 (1) ◽  
pp. 66-75 ◽  
Author(s):  
Flavio Carsughi ◽  
Achille Giacometti ◽  
Domenico Gazzillo
Keyword(s):  
Data Analysis ◽  
Small Angle ◽  
Small Angle Scattering ◽  
Scattering Data ◽  
Angle Scattering

Quality control of protein standards for molecular mass determinations by small-angle X-ray scattering

2010 ◽  
Vol 43 (2) ◽  
pp. 237-243 ◽  
Author(s):  
Shuji Akiyama
Keyword(s):  
Quality Control ◽  
Molecular Mass ◽  
Small Angle ◽  
Biological Macromolecules ◽  
Average Deviation ◽  
Saxs Data ◽  
X Ray ◽  
X Ray Scattering ◽  
Standard Quality ◽  
Ray Scattering

Small-angle X-ray scattering (SAXS) is a powerful technique with which to evaluate the size and shape of biological macromolecules in solution. Forward scattering intensity normalized relative to the particle concentration,I(0)/c, is useful as a good measure of molecular mass. A general method for deducing the molecular mass from SAXS data is to determine the ratio ofI(0)/cof a target protein to that of a standard protein with known molecular mass. The accuracy of this interprotein calibration is affected considerably by the monodispersity of the prepared standard, as well as by the precision in estimating its concentration. In the present study, chromatographic fractionation followed by hydrodynamic characterization is proposed as an effective procedure by which to prepare a series of monodispersed protein standards. The estimation of molecular mass within an average deviation of 8% is demonstrated using monodispersed bovine serum albumin as a standard. The present results demonstrate the importance of protein standard quality control in order to take full advantage of interprotein calibration.

Recent developments in small-angle X-ray scattering and hybrid method approaches for biomacromolecular solutions

2018 ◽  
Vol 2 (1) ◽  
pp. 69-79 ◽  
Author(s):  
Martin A. Schroer ◽  
Dmitri I. Svergun
Keyword(s):  
Small Angle ◽  
Scattering Data ◽  
Quality Data ◽  
Biological Macromolecules ◽  
Ambient Conditions ◽  
X Ray ◽  
X Ray Scattering ◽  
Analysis Methods ◽  
Recent Developments ◽  
Ray Scattering

Small-angle X-ray scattering (SAXS) has become a streamline method to characterize biological macromolecules, from small peptides to supramolecular complexes, in near-native solutions. Modern SAXS requires limited amounts of purified material, without the need for labelling, crystallization, or freezing. Dedicated beamlines at modern synchrotron sources yield high-quality data within or below several milliseconds of exposure time and are highly automated, allowing for rapid structural screening under different solutions and ambient conditions but also for time-resolved studies of biological processes. The advanced data analysis methods allow one to meaningfully interpret the scattering data from monodisperse systems, from transient complexes as well as flexible and heterogeneous systems in terms of structural models. Especially powerful are hybrid approaches utilizing SAXS with high-resolution structural techniques, but also with biochemical, biophysical, and computational methods. Here, we review the recent developments in the experimental SAXS practice and in analysis methods with a specific focus on the joint use of SAXS with complementary methods.

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