Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms

Cryogenic electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. However, automated identification of macromolecules inside cellular tomograms is challenged by noise and reconstruction artifacts, as well as the presence of...

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Bibliographic Details
Published in:	Nature methods Vol. 18; no. 11; pp. 1386 - 1394
Main Authors:	Moebel, Emmanuel, Martinez-Sanchez, Antonio, Lamm, Lorenz, Righetto, Ricardo D, Wietrzynski, Wojciech, Albert, Sahradha, Larivière, Damien, Fourmentin, Eric, Pfeffer, Stefan, Ortiz, Julio, Baumeister, Wolfgang, Peng, Tingying, Engel, Benjamin D, Kervrann, Charles
Format:	Journal Article
Language:	English
Published:	United States Nature Publishing Group 01.11.2021
Subjects:	Algorithms Annotations Artificial neural networks Chlamydomonas reinhardtii - metabolism Computer applications Cryoelectron Microscopy - methods Datasets Deep Learning Electron Microscope Tomography - methods Electrons Image Processing, Computer-Assisted - methods Machine learning Macromolecular Substances - chemistry Macromolecules Membranes Neural networks Neural Networks, Computer Oxygenase Photosystem II Photosystem II Protein Complex - chemistry Ribosomes Ribosomes - chemistry Ribulose-Bisphosphate Carboxylase - chemistry Spatial distribution Template matching
ISSN:	1548-7091, 1548-7105, 1548-7105
Online Access:	Get full text
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