Automatic data collection by a low-power microprocessor on the Italian buoy

1980 ◽  
Vol 3 (5) ◽  
pp. 517-526 ◽  
Author(s):  
G. Aprilesi ◽  
M. Menziani ◽  
M. R. Rivasi ◽  
M. Serafini
Keyword(s):  
Data Collection ◽  
Low Power ◽  
Automatic Data ◽  
Automatic Data Collection

scholarly journals Robust indexing for automatic data collection

2004 ◽  
Vol 37 (3) ◽  
pp. 399-409 ◽  
Author(s):  
Nicholas K. Sauter ◽  
Ralf W. Grosse-Kunstleve ◽  
Paul D. Adams
Keyword(s):  
Data Collection ◽  
High Throughput ◽  
Visual Inspection ◽  
The Novel ◽  
Automatic Data ◽  
X Ray ◽  
Alternative Approach ◽  
Automatic Data Collection ◽  
Diffraction Patterns ◽  
Improved Methods

Improved methods for indexing diffraction patterns from macromolecular crystals are presented. The novel procedures include a more robust way to verify the position of the incident X-ray beam on the detector, an algorithm to verify that the deduced lattice basis is consistent with the observations, and an alternative approach to identify the metric symmetry of the lattice. These methods help to correct failures commonly experienced during indexing, and increase the overall success rate of the process. Rapid indexing, without the need for visual inspection, will play an important role as beamlines at synchrotron sources prepare for high-throughput automation.

Automatic Data Collection Systems: Observed Benefits and Problems

1992 ◽  
Vol 12 (5) ◽  
pp. 57-68 ◽  
Author(s):  
Orinda Byrd Christoph ◽  
Scott P. Stevens ◽  
Richard T. Christoph
Keyword(s):  
Data Collection ◽  
Automatic Data ◽  
Automatic Data Collection

scholarly journals Automatic data collection for detecting travel behavior: the IPET platform

2018 ◽  
Vol 134 ◽  
pp. 421-426 ◽  
Author(s):  
Francesco Piras ◽  
Eleonora Sottile ◽  
Daniele Calli ◽  
Italo Meloni
Keyword(s):  
Data Collection ◽  
Travel Behavior ◽  
Automatic Data ◽  
Automatic Data Collection

scholarly journals ZOO: an automatic data-collection system for high-throughput structure analysis in protein microcrystallography

2019 ◽  
Vol 75 (2) ◽  
pp. 138-150 ◽  
Author(s):  
Kunio Hirata ◽  
Keitaro Yamashita ◽  
Go Ueno ◽  
Yoshiaki Kawano ◽  
Kazuya Hasegawa ◽  
...  
Keyword(s):  
Data Collection ◽  
Structural Information ◽  
Protein Crystal ◽  
Quality Data ◽  
Collection System ◽  
Automated Data Collection ◽  
Automatic Data ◽  
Data Collection System ◽  
Automatic Data Collection ◽  
Processing Techniques

Owing to the development of brilliant microfocus beamlines, rapid-readout detectors and sample changers, protein microcrystallography is rapidly becoming a popular technique for accessing structural information from complex biological samples. However, the method is time-consuming and labor-intensive and requires technical expertise to obtain high-resolution protein crystal structures. At SPring-8, an automated data-collection system named ZOO has been developed. This system enables faster data collection, facilitates advanced data-collection and data-processing techniques, and permits the collection of higher quality data. In this paper, the key features of the functionality put in place on the SPring-8 microbeam beamline BL32XU are described and the major advantages of this system are outlined. The ZOO system will be a major driving force in the evolution of the macromolecular crystallography beamlines at SPring-8.

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