By the same authors

From the same journal

From the same journal

Classification of crystallization outcomes using deep convolutional neural networks

Research output: Contribution to journalArticlepeer-review

Full text download(s)

Published copy (DOI)



Publication details

JournalPLOS one
DateAccepted/In press - 29 May 2018
DatePublished (current) - 20 Jun 2018
Issue number6
Number of pages15
Original languageEnglish


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.

    Research areas

  • Algorithms, Crystallization, Crystallography, X-Ray, Datasets as Topic, Image Processing, Computer-Assisted, Neural Networks (Computer)

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations