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- Title
DeepCentering: fully automated crystal centering using deep learning for macromolecular crystallography.
- Authors
Ito, Sho; Ueno, Go; Yamamoto, Masaki
- Abstract
High‐throughput protein crystallography using a synchrotron light source is an important method used in drug discovery. Beamline components for automated experiments including automatic sample changers have been utilized to accelerate the measurement of a number of macromolecular crystals. However, unlike cryo‐loop centering, crystal centering involving automated crystal detection is a difficult process to automate fully. Here, DeepCentering, a new automated crystal centering system, is presented. DeepCentering works using a convolutional neural network, which is a deep learning operation. This system achieves fully automated accurate crystal centering without using X‐ray irradiation of crystals, and can be used for fully automated data collection in high‐throughput macromolecular crystallography.
- Subjects
DEEP learning; CRYSTALLOGRAPHY; CRYSTALS; LIGHT sources; PROTEIN crystallography
- Publication
Journal of Synchrotron Radiation, 2019, Vol 26, Issue 4, p1361
- ISSN
0909-0495
- Publication type
Article
- DOI
10.1107/S160057751900434X