Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

A multi-model approach to assessing local and global cryo-EM map quality

Mark A. Herzik Jr., View ORCID ProfileJames S. Fraser, Gabriel C. Lander
doi: https://doi.org/10.1101/128561
Mark A. Herzik Jr.
1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California 92037, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James S. Fraser
2Department of Bioengineering and Therapeutic Science and California Institute for Quantitative Biology, University of California, San Francisco, San Francisco, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for James S. Fraser
Gabriel C. Lander
1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California 92037, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

There does not currently exist a standardized indicator of how well a cryo-EM-derived model represents the density from which it was generated. We present a straightforward methodology that utilizes freely available tools to generate a suite of independent models and to evaluate their convergence in an EM density. These analyses provide both a quantitative and qualitative assessment of the precision of the models and their representation of the density, respectively, while concurrently providing a platform for assessing both global and local EM map quality. We further use standardized datasets to provide an expected model–model agreement criterion for EM maps reported to be at 5 Å resolution or better. Associating multiple atomic models with a deposited EM map provides a rapid and accessible reporter of convergence, a strong indicator of highly resolved molecular detail, and is an important step toward an FSC-independent assessment of map and model quality.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted April 19, 2017.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
A multi-model approach to assessing local and global cryo-EM map quality
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
A multi-model approach to assessing local and global cryo-EM map quality
Mark A. Herzik Jr., James S. Fraser, Gabriel C. Lander
bioRxiv 128561; doi: https://doi.org/10.1101/128561
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
A multi-model approach to assessing local and global cryo-EM map quality
Mark A. Herzik Jr., James S. Fraser, Gabriel C. Lander
bioRxiv 128561; doi: https://doi.org/10.1101/128561

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Biophysics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4246)
  • Biochemistry (9176)
  • Bioengineering (6807)
  • Bioinformatics (24069)
  • Biophysics (12161)
  • Cancer Biology (9568)
  • Cell Biology (13847)
  • Clinical Trials (138)
  • Developmental Biology (7662)
  • Ecology (11739)
  • Epidemiology (2066)
  • Evolutionary Biology (15547)
  • Genetics (10673)
  • Genomics (14366)
  • Immunology (9517)
  • Microbiology (22916)
  • Molecular Biology (9135)
  • Neuroscience (49170)
  • Paleontology (358)
  • Pathology (1488)
  • Pharmacology and Toxicology (2584)
  • Physiology (3851)
  • Plant Biology (8353)
  • Scientific Communication and Education (1473)
  • Synthetic Biology (2302)
  • Systems Biology (6207)
  • Zoology (1304)