Classification of crystallization outcomes using deep convolutional neural networks.
Publication
, Journal Article
Bruno, AE; Charbonneau, P; Newman, J; Snell, EH; So, DR; Vanhoucke, V; Watkins, CJ; Williams, S; Wilson, J
Published in: PloS one
January 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 screening and the systematic analysis of crystallization experiments, this approach opens the door to both industrial and fundamental research applications.
Duke Scholars
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Published In
PloS one
DOI
EISSN
1932-6203
ISSN
1932-6203
Publication Date
January 2018
Volume
13
Issue
6
Start / End Page
e0198883
Related Subject Headings
- Neural Networks, Computer
- Image Processing, Computer-Assisted
- General Science & Technology
- Datasets as Topic
- Crystallography, X-Ray
- Crystallization
- Algorithms
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NLM
Bruno, A. E., Charbonneau, P., Newman, J., Snell, E. H., So, D. R., Vanhoucke, V., … Wilson, J. (2018). Classification of crystallization outcomes using deep convolutional neural networks. PloS One, 13(6), e0198883. https://doi.org/10.1371/journal.pone.0198883
Bruno, Andrew E., Patrick Charbonneau, Janet Newman, Edward H. Snell, David R. So, Vincent Vanhoucke, Christopher J. Watkins, Shawn Williams, and Julie Wilson. “Classification of crystallization outcomes using deep convolutional neural networks.” PloS One 13, no. 6 (January 2018): e0198883. https://doi.org/10.1371/journal.pone.0198883.
Bruno AE, Charbonneau P, Newman J, Snell EH, So DR, Vanhoucke V, et al. Classification of crystallization outcomes using deep convolutional neural networks. PloS one. 2018 Jan;13(6):e0198883.
Bruno, Andrew E., et al. “Classification of crystallization outcomes using deep convolutional neural networks.” PloS One, vol. 13, no. 6, Jan. 2018, p. e0198883. Epmc, doi:10.1371/journal.pone.0198883.
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. 2018 Jan;13(6):e0198883.
Published In
PloS one
DOI
EISSN
1932-6203
ISSN
1932-6203
Publication Date
January 2018
Volume
13
Issue
6
Start / End Page
e0198883
Related Subject Headings
- Neural Networks, Computer
- Image Processing, Computer-Assisted
- General Science & Technology
- Datasets as Topic
- Crystallography, X-Ray
- Crystallization
- Algorithms