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  An integration of fast alignment and maximum-likelihood methods for electron subtomogram averaging and classification

Zhao, Y., Zeng, X., Guo, Q., & Xu, M. (2018). An integration of fast alignment and maximum-likelihood methods for electron subtomogram averaging and classification. Bioinformatics, 34(13), i227-i236.

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© The Author(s) 2018. Published by Oxford University Press.

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 Creators:
Zhao, Yixiu1, Author
Zeng, Xiangrui1, Author
Guo, Qiang2, Author              
Xu, Min1, Author
Affiliations:
1external, ou_persistent22              
2Baumeister, Wolfgang / Molecular Structural Biology, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565142              

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Free keywords: IN-SITU; TOMOGRAPHY; MICROSCOPY; COMPLEXESBiochemistry & Molecular Biology; Biotechnology & Applied Microbiology; Computer Science; Mathematical & Computational Biology; Mathematics;
 Abstract: Motivation: Cellular Electron CryoTomography (CECT) is an emerging 3D imaging technique that visualizes subcellular organization of single cells at sub-molecular resolution and in near-native state. CECT captures large numbers of macromolecular complexes of highly diverse structures and abundances. However, the structural complexity and imaging limits complicate the systematic de novo structural recovery and recognition of these macromolecular complexes. Efficient and accurate reference-free subtomogram averaging and classification represent the most critical tasks for such analysis. Existing subtomogram alignment based methods are prone to the missing wedge effects and low signal-to-noise ratio (SNR). Moreover, existing maximum-likelihood based methods rely on integration operations, which are in principle computationally infeasible for accurate calculation. Results: Built on existing works, we propose an integrated method, Fast Alignment Maximum Likelihood method (FAML), which uses fast subtomogram alignment to sample sub-optimal rigid transformations. The transformations are then used to approximate integrals for maximum-likelihood update of subtomogram averages through expectation-maximization algorithm. Our tests on simulated and experimental subtomograms showed that, compared to our previously developed fast alignment method (FA), FAML is significantly more robust to noise and missing wedge effects with moderate increases of computation cost. Besides, FAML performs well with significantly fewer input subtomograms when the FA method fails. Therefore, FAML can serve as a key component for improved construction of initial structuralmodels frommacromolecules captured by CECT.

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Language(s): eng - English
 Dates: 2018
 Publication Status: Published in print
 Pages: 10
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Degree: -

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Title: 26th Annual Conference on Intelligent Systems for Molecular Biology (ISMB)
Place of Event: Chicago, IL
Start-/End Date: 2018-07-06 - 2018-07-10

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Title: Bioinformatics
  Subtitle : ISMB 2018 Proceedings July 6 to July 10, 2018, Chicago, IL, United States
Source Genre: Journal
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Publ. Info: Oxford : Oxford University Press
Pages: - Volume / Issue: 34 (13) Sequence Number: - Start / End Page: i227 - i236 Identifier: ISSN: 1367-4803
CoNE: https://pure.mpg.de/cone/journals/resource/954926969991