Εξειδίκευση τύπου :	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	Self-supervised learning for generalizable particle picking in cryo-EM micrographs
Δημιουργός/Συγγραφέας:	Zamanos, Andreas Koromilas, Panagiotis Bouritsas, Giorgos [EL] Καστρίτης, Παναγιώτης[EN] Kastritis, Panagiotis Panagakis, Yannis
Ημερομηνία:	2025-06-28
Γλώσσα:	Αγγλικά
ISSN:	26672375
DOI:	10.1016/j.crmeth.2025.101089
Άλλο:	40628274
Περίληψη:	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 representation. Evaluation across different EMPIAR datasets demonstrates that cryo-EMMAE outperforms state-of-the-art supervised methods in terms of generalization capabilities. Importantly, our method showcases consistent performance, independent of the dataset used for training. Additionally, cryo-EMMAE is data efficient, as we experimentally observe that it converges with as few as five micrographs. Further, 3D reconstruction results indicate that our method has superior performance in reconstructing the volumes in both single-particle datasets and multi-particle micrographs derived from cell extracts. Our results underscore the potential of self-supervised learning in advancing cryo-EM image analysis, offering an alternative for more efficient and cost-effective structural biology research. Code is available at https://github.com/azamanos/Cryo-EMMAE.
Τίτλος πηγής δημοσίευσης:	Cell reports methods
Θεματική Κατηγορία:	[EL] Δομική Βιολογία[EN] Structural Biology [EL] Βιοπληροφορική[EN] Bioinformatics [EL] Οπτική. Φώς[EN] Optics. Light [EL] Κυτταρολογία[EN] Cytology
Λέξεις-Κλειδιά:	CP: computational biology CP: imaging applied machine learning cellular homogenates cryo-EM masked autoencoder micrographs native cell extracts particle picking protein complexes proteins self-supervised learning
Κάτοχος πνευματικών δικαιωμάτων:	© 2025 The Authors. Published by Elsevier Inc. All rights reserved.
Όροι και προϋποθέσεις δικαιωμάτων:	This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Ηλεκτρονική διεύθυνση στον εκδότη (link):	https://doi.org/10.1016/j.crmeth.2025.101089
Εμφανίζεται στις συλλογές:	Ινστιτούτο Χημικής Βιολογίας - Επιστημονικό έργο