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Unsupervised particle sorting for high-resolution single-particle cryo-EM

Publication ,  Journal Article
Zhou, Y; Moscovich, A; Bendory, T; Bartesaghi, A
Published in: Inverse Problems
January 1, 2020

Single-particle cryo-electron microscopy (EM) has become a popular technique for determining the structure of challenging biomolecules that are inaccessible to other technologies. Recent advances in automation, both in data collection and data processing, have significantly lowered the barrier for non-expert users to successfully execute the structure determination workflow. Many critical data processing steps, however, still require expert user intervention in order to converge to the correct high-resolution structure. In particular, strategies to identify homogeneous populations of particles rely heavily on subjective criteria that are not always consistent or reproducible among different users. Here, we explore the use of unsupervised strategies for particle sorting that are compatible with the autonomous operation of the image processing pipeline. More specifically, we show that particles can be successfully sorted based on a simple statistical model for the distribution of scores assigned during refinement. This represents an important step towards the development of automated workflows for protein structure determination using single-particle cryo-EM.

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Published In

Inverse Problems

DOI

EISSN

1361-6420

ISSN

0266-5611

Publication Date

January 1, 2020

Volume

36

Issue

4

Related Subject Headings

  • Applied Mathematics
  • 4904 Pure mathematics
  • 4901 Applied mathematics
  • 0105 Mathematical Physics
  • 0102 Applied Mathematics
  • 0101 Pure Mathematics
 

Citation

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Zhou, Y., Moscovich, A., Bendory, T., & Bartesaghi, A. (2020). Unsupervised particle sorting for high-resolution single-particle cryo-EM. Inverse Problems, 36(4). https://doi.org/10.1088/1361-6420/ab5ec8
Zhou, Y., A. Moscovich, T. Bendory, and A. Bartesaghi. “Unsupervised particle sorting for high-resolution single-particle cryo-EM.” Inverse Problems 36, no. 4 (January 1, 2020). https://doi.org/10.1088/1361-6420/ab5ec8.
Zhou Y, Moscovich A, Bendory T, Bartesaghi A. Unsupervised particle sorting for high-resolution single-particle cryo-EM. Inverse Problems. 2020 Jan 1;36(4).
Zhou, Y., et al. “Unsupervised particle sorting for high-resolution single-particle cryo-EM.” Inverse Problems, vol. 36, no. 4, Jan. 2020. Scopus, doi:10.1088/1361-6420/ab5ec8.
Zhou Y, Moscovich A, Bendory T, Bartesaghi A. Unsupervised particle sorting for high-resolution single-particle cryo-EM. Inverse Problems. 2020 Jan 1;36(4).
Journal cover image

Published In

Inverse Problems

DOI

EISSN

1361-6420

ISSN

0266-5611

Publication Date

January 1, 2020

Volume

36

Issue

4

Related Subject Headings

  • Applied Mathematics
  • 4904 Pure mathematics
  • 4901 Applied mathematics
  • 0105 Mathematical Physics
  • 0102 Applied Mathematics
  • 0101 Pure Mathematics