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Classification of crystallization outcomes using deep convolutional neural networks

Andrew E. Bruno
Patrick Charbonneau
Janet Newman
Edward H. Snell
David Richard So
Christopher J. Watkins
Shawn Williams
Julie Wilson
PLOS One (2018)


The Machine Recognition of Crystallization Outcomes (MARCO) initiative has assembled roughly half a million annotated images of macromolecular crystallization experiments from various sources and setups. Here, state-of-the-art machine learning algorithms are trained and tested on different parts of this data set. We find that more than 94% of the test images can be correctly labeled, irrespective of their experimental origin. Because crystal recognition is key to high-density sampling and the systematic analysis of crystallization experiments, this approach opens the door to both industrial and fundamental research applications.