2019Wagner Cryolo
Citation
Wagner, T.; Merino, F.; Stabrin, M.; Moriya, T.; Antoni, C.; Apelbaum, A.; Hagel, P.; Sitsel, O.; Raisch, T.; Prumbaum, D.; Quentin, D.; Roderer, D.; Tacke, S.; Siebolds, B.; Schubert, E.; Shaikh, T. R.; Lill, P.; Gatsogiannis, C. & Raunser, S. SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM. Communications biology, 2019 , 2 , 218
Abstract
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.
Keywords
Links
https://www.nature.com/articles/s42003-019-0437-z.pdf