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Measurement of the intrinsic variability within protein crystals: implications for sample‐evaluation and data‐collection strategies
Author(s) -
Bowler Michael G.,
Bowler Matthew W.
Publication year - 2014
Publication title -
acta crystallographica section f
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.572
H-Index - 37
ISSN - 2053-230X
DOI - 10.1107/s2053230x13032007
Subject(s) - data collection , metric (unit) , crystal (programming language) , sample (material) , protein crystallization , automation , scale (ratio) , oscillation (cell signaling) , computer science , variation (astronomy) , data science , data mining , statistics , physics , mathematics , chemistry , engineering , operations management , mechanical engineering , biochemistry , quantum mechanics , crystallization , thermodynamics , programming language , astrophysics
The advent of micro‐focused X‐ray beams has led to the development of a number of advanced methods of sample evaluation and data collection. In particular, multiple‐position data‐collection and helical oscillation strategies are now becoming commonplace in order to alleviate the problems associated with radiation damage. However, intra‐crystal and inter‐crystal variation means that it is not always obvious on which crystals or on which region or regions of a crystal these protocols should be performed. For the automation of this process for large‐scale screening, and to provide an indication of the best strategy for data collection, a metric of crystal variability could be useful. Here, measures of the intrinsic variability within protein crystals are presented and their implications for optimal data‐collection strategies are discussed.