Classification of crystallization outcomes using deep convolutional neural networks.
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 screening and the systematic analysis of crystallization experiments, this approach opens the door to both industrial and fundamental research applications.
Bruno, AE; Charbonneau, P; Newman, J; Snell, EH; So, DR; Vanhoucke, V; Watkins, CJ; Williams, S; Wilson, J
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