A hybrid YOLO-UNet3D framework for automated protein particle annotation in Cryo-ET images

A hybrid YOLO-UNet3D framework for automated protein particle annotation in Cryo-ET images

Abstract Accurate localization and identification of protein complexes in cryo-electron tomography (cryo-ET) volumes are essential for understanding cellular functions and disease mechanisms. However, automated annotation of these macromolecular assemblies remains challenging due to low signal-to-no...

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Bibliographic Details
Main Authors: Ziyang Liu, Chunhong Yuan, Zixin Zhang, Xiang Zhou, Xiangyu Li, Zhen Tian, Yuting Pei, Zuowen Jiang, Zhikui Tian
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Cryo-electron tomography
Protein particle detection
YOLO
UNet3D
Deep learning
Density clustering
Online Access:https://doi.org/10.1038/s41598-025-09522-w
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https://doi.org/10.1038/s41598-025-09522-w

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