crYOLO
Description
Automated screening of CryoEM specimens
Detailed example
Inputs are low magnification cryoEM imaging data and, optionally, manually selected targets; outputs are automatically selected imaging targets.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
This tool is an open-source machine learning-based particle picker (https://cryolo.readthedocs.io/en/stable/). This tool automatically picks targets based on its general model or an adapted model using small number of manually selected particles. It is utilized by the Cryo-EM core in support of research projects within NIEHS DIR and DTT laboratories.
Controls / human review
ATO: No; PIA: Not published
Data needed
Models were initially trained using publicly available data, further training may be performed using data set being analyzed.