https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2019Wagner_Cryolo 2026-05-24T21:07:10Z Revision history for this page on the wiki MediaWiki 1.44.2 https://3demmethods.i2pc.es/index.php?title=2019Wagner_Cryolo&diff=3543&oldid=prev 2019-07-03T20:20:17Z

<p>Created page with &quot;== 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....&quot;</p> <p><b>New page</b></p><div>== Citation ==<br /> <br /> 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. &amp; Raunser, S.<br /> SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM. <br /> Communications biology, 2019 , 2 , 218 <br /> <br /> == Abstract ==<br /> <br /> 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.<br /> <br /> == Keywords ==<br /> <br /> == Links ==<br /> <br /> https://www.nature.com/articles/s42003-019-0437-z.pdf<br /> <br /> == Related software ==<br /> <br /> == Related methods ==<br /> <br /> == Comments ==</div>

WikiSysop