Classification of crystallization outcomes using deep convolutional neural networks

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Authors Andrew E. Bruno, Shawn Williams, Edward H. Snell, Patrick Charbonneau, David R. So, Julie Wilson, Janet Newman, Christopher J. Watkins, Vincent Vanhoucke
Journal/Conference Name PLoS ONE
Paper Category
Paper Abstract 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.
Date of publication 2018
Code Programming Language Multiple

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