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  Autofocused 3D Classification of Cryoelectron Subtomograms

Chen, Y., Pfeffer, S., Jesus Fernandez, J., Sorzano, C. O. S., & Förster, F. (2014). Autofocused 3D Classification of Cryoelectron Subtomograms. STRUCTURE, 22(10), 1528-1537. doi:10.1016/j.str.2014.08.007.

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 Creators:
Chen, Yuxiang1, Author              
Pfeffer, Stefan1, Author              
Jesus Fernandez, Jose2, Author
Sorzano, Carlos Oscar S.2, Author
Förster, Friedrich1, Author              
Affiliations:
1Förster, Friedrich / Modeling of Protein Complexes, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565148              
2external, ou_persistent22              

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Free keywords: IN-SITU; ELECTRON TOMOGRAPHY; ALIGNMENT; ALGORITHM; RIBOSOMES; CELLS; FFTS
 Abstract: Classification of subtomograms obtained by cryoelectron tomography (cryo-ET) is a powerful approach to study the conformational landscapes of macromolecular complexes in situ. Major challenges in subtomogram classification are the low signal-to-noise ratio (SNR) of cryo-tomograms, their incomplete angular sampling, the unknown number of classes and the typically unbalanced abundances of structurally distinct complexes. Here, we propose a clustering algorithm named AC3D that is based on a similarity measure, which automatically focuses on the areas of major structural discrepancy between respective subtomogram class averages. Furthermore, we incorporate a spherical-harmonics-based fast subtomogram alignment algorithm, which provides a significant speedup. Assessment of our approach on simulated data sets indicates substantially increased classification accuracy of the presented method compared to two state-of-the-art approaches. Application to experimental subtomograms depicting endoplasmic-reticulum-associated ribosomal particles shows that AC3D is well suited to deconvolute the compositional heterogeneity of macromolecular complexes in situ.

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Language(s): eng - English
 Dates: 2014
 Publication Status: Published in print
 Pages: 10
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000343586000017
DOI: 10.1016/j.str.2014.08.007
 Degree: -

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Title: STRUCTURE
Source Genre: Journal
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Publ. Info: 600 TECHNOLOGY SQUARE, 5TH FLOOR, CAMBRIDGE, MA 02139 USA : CELL PRESS
Pages: - Volume / Issue: 22 (10) Sequence Number: - Start / End Page: 1528 - 1537 Identifier: ISSN: 0969-2126