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.
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Department of Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences,Pennsylvania State UniversityDepartment of Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences,Pennsylvania State University
Jean-Paul Armache
Yifan Cheng
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Howard Hughes Medical Institute, University of California San Francisco
Department of Biochemistry and Biophysics,University of California San FranciscoDepartment of Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences,Pennsylvania State University