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Curr Opin Microbiol. 2018 Jun;43:1-8. doi: 10.1016/j.mib.2017.10.005. Epub 2017 Oct 31.

Big data in cryoEM: automated collection, processing and accessibility of EM data.

Author information

1
The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA.
2
The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA.
3
Life Sciences Institute and Department of Biological Chemistry, University of Michigan, Ann Arbor, MI 48109, USA.
4
The National Resource for Automated Molecular Microscopy, Simons Electron Microscopy Center, New York Structural Biology Center, 89 Convent Ave, New York, NY 10027, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. Electronic address: bcarr@nysbc.org.

Abstract

The scope and complexity of cryogenic electron microscopy (cryoEM) data has greatly increased, and will continue to do so, due to recent and ongoing technical breakthroughs that have led to much improved resolutions for macromolecular structures solved using this method. This big data explosion includes single particle data as well as tomographic tilt series, both generally acquired as direct detector movies of ∼10-100 frames per image or per tilt-series. We provide a brief survey of the developments leading to the current status, and describe existing cryoEM pipelines, with an emphasis on the scope of data acquisition, methods for automation, and use of cloud storage and computing.

PMID:
29100109
PMCID:
PMC6067001
[Available on 2019-06-01]
DOI:
10.1016/j.mib.2017.10.005

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