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Machine learning-based real-time object locator/evaluator for cryo-EM data collection.


ABSTRACT: In cryo-electron microscopy (cryo-EM) data collection, locating a target object is error-prone. Here, we present a machine learning-based approach with a real-time object locator named yoneoLocr using YOLO, a well-known object detection system. Implementation shows its effectiveness in rapidly and precisely locating carbon holes in single particle cryo-EM and in locating crystals and evaluating electron diffraction (ED) patterns in automated cryo-electron crystallography (cryo-EX) data collection. The proposed approach will advance high-throughput and accurate data collection of images and diffraction patterns with minimal human operation.

SUBMITTER: Yonekura K 

PROVIDER: S-EPMC8423793 | biostudies-literature |

REPOSITORIES: biostudies-literature

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