Best practices for high data-rate macromolecular crystallography (HDRMX)

In macromolecular crystallography, higher flux, smaller beams, and faster detectors open the door to experiments with very large numbers of very small samples that can reveal polymorphs and dynamics but require re-engineering of approaches to the clustering of images both at synchrotrons and XFELs (...

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Bibliographic Details
Main Authors: Herbert J. Bernstein, Lawrence C. Andrews, Jorge A. Diaz Jr., Jean Jakoncic, Thu Nguyen, Nicholas K. Sauter, Alexei S. Soares, Justin Y. Wei, Maciej R. Wlodek, Mario A. Xerri
Format: Article
Language:English
Published: AIP Publishing LLC and ACA 2020-01-01
Series:Structural Dynamics
Online Access:http://dx.doi.org/10.1063/1.5128498
Description
Summary:In macromolecular crystallography, higher flux, smaller beams, and faster detectors open the door to experiments with very large numbers of very small samples that can reveal polymorphs and dynamics but require re-engineering of approaches to the clustering of images both at synchrotrons and XFELs (X-ray free electron lasers). The need for the management of orders of magnitude more images and limitations of file systems favor a transition from simple one-file-per-image systems such as CBF to image container systems such as HDF5. This further increases the load on computers and networks and requires a re-examination of the presentation of metadata. In this paper, we discuss three important components of this problem—improved approaches to the clustering of images to better support experiments on polymorphs and dynamics, recent and upcoming changes in metadata for Eiger images, and software to rapidly validate images in the revised Eiger format.
ISSN:2329-7778