Evidence map›Paper›PMID 32153279›Full record

ArticleJournal of synchrotron radiation2020

Seed-skewness algorithm for X-ray diffraction signal detection in time-resolved synchrotron Laue photocrystallography.

Dariusz Szarejko, Radosław Kamiński, Piotr Łaski, Katarzyna N Jarzembska

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Article in Journal of synchrotron radiation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Dariusz SzarejkoDepartment of Chemistry, University of Warsaw, Żwirki i Wigury 101, 02-089 Warsaw, Poland.
Radosław KamińskiDepartment of Chemistry, University of Warsaw, Żwirki i Wigury 101, 02-089 Warsaw, Poland.
Piotr ŁaskiDepartment of Chemistry, University of Warsaw, Żwirki i Wigury 101, 02-089 Warsaw, Poland.
Katarzyna N JarzembskaDepartment of Chemistry, University of Warsaw, Żwirki i Wigury 101, 02-089 Warsaw, Poland.

Funding

BioCARS: A Synchrotron Structure Biology ResourceR24GM111072 · NIGMS · UNIVERSITY OF CHICAGO · PI MOFFAT, JOHN KEITH · 2013 to 2016
$2.3M
NIGMS NIH HHS R24 GM111072NIGMS NIH HHS R24GM111072
6 · The paper itself

Abstract

A one-dimensional seed-skewness algorithm adapted for X-ray diffraction signal detection is presented and discussed. The method, primarily designed for photocrystallographic time-resolved Laue data processing, was shown to work well for the type of data collected at the Advanced Photon Source and European Synchrotron Radiation Facility. Nevertheless, it is also applicable in the case of standard single-crystal X-ray diffraction data. The reported algorithm enables reasonable separation of signal from the background in single one-dimensional data vectors as well as the capability to determine small changes of reflection shapes and intensities resulting from exposure of the sample to laser light. Otherwise, the procedure is objective, and relies only on skewness computation and its subsequent minimization. The new algorithm was proved to yield comparable results to the Kruskal-Wallis test method [Kalinowski, J. A. et al. (2012). J. Synchrotron Rad. 19, 637], while the processing takes a similar amount of time. Importantly, in contrast to the Kruskal-Wallis test, the reported seed-skewness approach does not need redundant input data, which allows for faster data collections and wider applications. Furthermore, as far as the structure refinement is concerned, the reported algorithm leads to the excited-state geometry closest to the one modelled using the quantum-mechanics/molecular-mechanics approach reported previously [Jarzembska, K. N. et al. (2014). Inorg. Chem. 53, 10594], when the t and s algorithm parameters are set to the recommended values of 0.2 and 3.0, respectively.

Indexed as

background estimationdata processingskewnessstatistical analysisX-ray diffraction

Identifiers

PMID32153279
PMCPMC7064106

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.