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PyMDA: microcrystal data assembly using Python

The recent developments at microdiffraction X-ray beamlines are making microcrystals of macromolecules appealing subjects for routine structural analysis. Microcrystal diffraction data collected at synchrotron microdiffraction beamlines may be radiation damaged with incomplete data per microcrystal...

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Detalles Bibliográficos
Autores principales: Takemaru, Lina, Guo, Gongrui, Zhu, Ping, Hendrickson, Wayne A., McSweeney, Sean, Liu, Qun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6998775/
https://www.ncbi.nlm.nih.gov/pubmed/32047415
http://dx.doi.org/10.1107/S160057671901673X
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author Takemaru, Lina
Guo, Gongrui
Zhu, Ping
Hendrickson, Wayne A.
McSweeney, Sean
Liu, Qun
author_facet Takemaru, Lina
Guo, Gongrui
Zhu, Ping
Hendrickson, Wayne A.
McSweeney, Sean
Liu, Qun
author_sort Takemaru, Lina
collection PubMed
description The recent developments at microdiffraction X-ray beamlines are making microcrystals of macromolecules appealing subjects for routine structural analysis. Microcrystal diffraction data collected at synchrotron microdiffraction beamlines may be radiation damaged with incomplete data per microcrystal and with unit-cell variations. A multi-stage data assembly method has previously been designed for microcrystal synchrotron crystallography. Here the strategy has been implemented as a Python program for microcrystal data assembly (PyMDA). PyMDA optimizes microcrystal data quality including weak anomalous signals through iterative crystal and frame rejections. Beyond microcrystals, PyMDA may be applicable for assembling data sets from larger crystals for improved data quality.
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spelling pubmed-69987752020-02-11 PyMDA: microcrystal data assembly using Python Takemaru, Lina Guo, Gongrui Zhu, Ping Hendrickson, Wayne A. McSweeney, Sean Liu, Qun J Appl Crystallogr Computer Programs The recent developments at microdiffraction X-ray beamlines are making microcrystals of macromolecules appealing subjects for routine structural analysis. Microcrystal diffraction data collected at synchrotron microdiffraction beamlines may be radiation damaged with incomplete data per microcrystal and with unit-cell variations. A multi-stage data assembly method has previously been designed for microcrystal synchrotron crystallography. Here the strategy has been implemented as a Python program for microcrystal data assembly (PyMDA). PyMDA optimizes microcrystal data quality including weak anomalous signals through iterative crystal and frame rejections. Beyond microcrystals, PyMDA may be applicable for assembling data sets from larger crystals for improved data quality. International Union of Crystallography 2020-02-01 /pmc/articles/PMC6998775/ /pubmed/32047415 http://dx.doi.org/10.1107/S160057671901673X Text en © Lina Takemarua et al. 2020 http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.http://creativecommons.org/licenses/by/4.0/
spellingShingle Computer Programs
Takemaru, Lina
Guo, Gongrui
Zhu, Ping
Hendrickson, Wayne A.
McSweeney, Sean
Liu, Qun
PyMDA: microcrystal data assembly using Python
title PyMDA: microcrystal data assembly using Python
title_full PyMDA: microcrystal data assembly using Python
title_fullStr PyMDA: microcrystal data assembly using Python
title_full_unstemmed PyMDA: microcrystal data assembly using Python
title_short PyMDA: microcrystal data assembly using Python
title_sort pymda: microcrystal data assembly using python
topic Computer Programs
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6998775/
https://www.ncbi.nlm.nih.gov/pubmed/32047415
http://dx.doi.org/10.1107/S160057671901673X
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