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  High-throughput subtomogram alignment and classification by Fourier space constrained fast volumetric matching

Xu, M., Beck, M., & Alber, F. (2012). High-throughput subtomogram alignment and classification by Fourier space constrained fast volumetric matching. Journal of Structural Biology, 178(2), 152-164. doi:10.1016/j.jsb.2012.02.014.

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 Urheber:
Xu, Min1, Autor
Beck, Martin2, Autor                 
Alber, Frank1, Autor
Affiliations:
1External Organizations, ou_persistent22              
2European Molecular Biology Laboratory (EMBL), Heidelberg, Germany, ou_persistent22              

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Schlagwörter: Cryoelectron Microscopy, Electron Microscope Tomography, Fourier Analysis, Image Processing, Computer-Assisted, Software
 Zusammenfassung: Cryo-electron tomography allows the visualization of macromolecular complexes in their cellular environments in close-to-live conditions. The nominal resolution of subtomograms can be significantly increased when individual subtomograms of the same kind are aligned and averaged. A vital step for such a procedure are algorithms that speedup subtomogram alignment and improve its accuracy to allow reference-free subtomogram classifications. Such methods will facilitate automation of tomography analysis and overall high throughput in the data processing. Building on previous work, here we propose a fast rotational alignment method that uses the Fourier equivalent form of a popular constrained correlation measure that considers missing wedge corrections and density variances in the subtomograms. The fast rotational search is based on 3D volumetric matching, which improves the rotational alignment accuracy in particular for highly distorted subtomograms with low SNR and tilt angle ranges in comparison to fast rotational matching of projected 2D spherical images. We further integrate our fast rotational alignment method in a reference-free iterative subtomogram classification scheme, and propose a local feature enhancement strategy in the classification process. As a proof of principle, we can demonstrate that the automatic method can successfully classify a large number of experimental subtomograms without the need of a reference structure.

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Sprache(n): eng - English
 Datum: 20122012-03-072012-05
 Publikationsstatus: Erschienen
 Seiten: 13
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.jsb.2012.02.014
BibTex Citekey: xu_high-throughput_2012
 Art des Abschluß: -

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Titel: Journal of Structural Biology
  Kurztitel : J. Struct. Biol.
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: San Diego, CA : Elsevier
Seiten: - Band / Heft: 178 (2) Artikelnummer: - Start- / Endseite: 152 - 164 Identifikator: ISSN: 1047-8477
CoNE: https://pure.mpg.de/cone/journals/resource/954922650160