Self-supervised learning for generalizable particle picking in cryo-EM micrographs

Summary: We present cryoelectron microscopy masked autoencoder (cryo-EMMAE), a self-supervised method designed to overcome the need for manually annotated cryo-EM data. cryo-EMMAE leverages the representation space of a masked autoencoder to pick particle pixels through clustering of the MAE latent...

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Bibliografiska uppgifter

Huvudupphov:	Andreas Zamanos, Panagiotis Koromilas, Giorgos Bouritsas, Panagiotis L. Kastritis, Yannis Panagakis
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	Elsevier 2025-07-01
Serie:	Cell Reports: Methods
Ämnen:	CP: computational biology CP: imaging
Länkar:	http://www.sciencedirect.com/science/article/pii/S2667237525001250
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