Publications [#337004] of Patrick Charbonneau

Papers Published

1. Bruno, AE; Charbonneau, P; Newman, J; Snell, EH; So, DR; Vanhoucke, V; Watkins, CJ; Williams, S; Wilson, J, Classification of crystallization outcomes using deep convolutional neural networks., PloS one, vol. 13 no. 6 (January, 2018), pp. e0198883 [doi]
   (last updated on 2024/04/24)

   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.