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SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM.

Thorsten WagnerFelipe MerinoMarkus StabrinToshio MoriyaClaudia AntoniAmir ApelbaumPhiline HagelOleg SitselTobias RaischDaniel PrumbaumDennis QuentinDaniel RodererSebastian TackeBirte SieboldsEvelyn SchubertTanvir R ShaikhPascal LillChristos GatsogiannisStefan Raunser
Published in: Communications biology (2019)
Selecting particles from digital micrographs is an essential step in single-particle electron cryomicroscopy (cryo-EM). As manual selection of complete datasets-typically comprising thousands of particles-is a tedious and time-consuming process, numerous automatic particle pickers have been developed. However, non-ideal datasets pose a challenge to particle picking. Here we present the particle picking software crYOLO which is based on the deep-learning object detection system You Only Look Once (YOLO). After training the network with 200-2500 particles per dataset it automatically recognizes particles with high recall and precision while reaching a speed of up to five micrographs per second. Further, we present a general crYOLO network able to pick from previously unseen datasets, allowing for completely automated on-the-fly cryo-EM data preprocessing during data acquisition. crYOLO is available as a standalone program under http://sphire.mpg.de/ and is distributed as part of the image processing workflow in SPHIRE.
Keyphrases
  • deep learning
  • machine learning
  • electronic health record
  • artificial intelligence
  • convolutional neural network
  • big data
  • high throughput
  • high resolution
  • mass spectrometry