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Decision making in xia2

xia2 is an expert system for the automated reduction of macromolecular crystallography (MX) data employing well trusted existing software. The system can process a full MX data set consisting of one or more sequences of images at one or more wavelengths from images to structure-factor amplitudes wit...

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Detalles Bibliográficos
Autores principales: Winter, Graeme, Lobley, Carina M. C., Prince, Stephen M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3689529/
https://www.ncbi.nlm.nih.gov/pubmed/23793152
http://dx.doi.org/10.1107/S0907444913015308
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author Winter, Graeme
Lobley, Carina M. C.
Prince, Stephen M.
author_facet Winter, Graeme
Lobley, Carina M. C.
Prince, Stephen M.
author_sort Winter, Graeme
collection PubMed
description xia2 is an expert system for the automated reduction of macromolecular crystallography (MX) data employing well trusted existing software. The system can process a full MX data set consisting of one or more sequences of images at one or more wavelengths from images to structure-factor amplitudes with no user input. To achieve this many decisions are made, the rationale for which is described here. In addition, it is critical to support the testing of hypotheses and to allow feedback of results from later stages in the analysis to earlier points where decisions were made: the flexible framework employed by xia2 to support this feedback is summarized here. While the decision-making protocols described here were developed for xia2, they are equally applicable to interactive data reduction.
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spelling pubmed-36895292013-06-28 Decision making in xia2 Winter, Graeme Lobley, Carina M. C. Prince, Stephen M. Acta Crystallogr D Biol Crystallogr Research Papers xia2 is an expert system for the automated reduction of macromolecular crystallography (MX) data employing well trusted existing software. The system can process a full MX data set consisting of one or more sequences of images at one or more wavelengths from images to structure-factor amplitudes with no user input. To achieve this many decisions are made, the rationale for which is described here. In addition, it is critical to support the testing of hypotheses and to allow feedback of results from later stages in the analysis to earlier points where decisions were made: the flexible framework employed by xia2 to support this feedback is summarized here. While the decision-making protocols described here were developed for xia2, they are equally applicable to interactive data reduction. International Union of Crystallography 2013-06-18 /pmc/articles/PMC3689529/ /pubmed/23793152 http://dx.doi.org/10.1107/S0907444913015308 Text en © Winter et al. 2013 http://creativecommons.org/licenses/by/2.0/uk/ This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.
spellingShingle Research Papers
Winter, Graeme
Lobley, Carina M. C.
Prince, Stephen M.
Decision making in xia2
title Decision making in xia2
title_full Decision making in xia2
title_fullStr Decision making in xia2
title_full_unstemmed Decision making in xia2
title_short Decision making in xia2
title_sort decision making in xia2
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3689529/
https://www.ncbi.nlm.nih.gov/pubmed/23793152
http://dx.doi.org/10.1107/S0907444913015308
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