CaltechAUTHORS
Published December 2022 | Version public
Journal Article Metadata-only

Smart data collection for CryoEM

Creators

  • 1. ROR icon New York Structural Biology Center
  • 2. ROR icon University of Washington
  • 3. ROR icon National Institute of Environmental Health Sciences
  • 4. ROR icon MRC Laboratory of Molecular Biology
  • 5. ROR icon California Institute of Technology
  • 6. ROR icon Northwestern University
  • 7. ROR icon Massachusetts Institute of Technology
  • 8. ROR icon SLAC National Accelerator Laboratory
  • 9. ROR icon University of California, San Francisco
  • 10. ROR icon University of Michigan–Ann Arbor
  • 11. ROR icon New York University
  • 12. ROR icon National Center for Biotechnology
  • 13. ROR icon Florida State University
  • 14. ROR icon University of North Carolina at Chapel Hill

Abstract

This report provides an overview of the discussions, presentations, and consensus thinking from the Workshop on Smart Data Collection for CryoEM held at the New York Structural Biology Center on April 6–7, 2022. The goal of the workshop was to address next generation data collection strategies that integrate machine learning and real-time processing into the workflow to reduce or eliminate the need for operator intervention.

Additional Information

We are grateful for financial support for this workshop from NIH NIGMS GM103310, Simons Foundation (SF349247), and Thermo Fisher Scientific.

Additional details

Identifiers

Eprint ID
118317
Resolver ID
CaltechAUTHORS:20221212-796622400.30

Funding

NIH
GM103310
Simons Foundation
SF349247
Thermo Fisher Scientific

Dates

Created
2023-01-13
Created from EPrint's datestamp field
Updated
2023-01-17
Created from EPrint's last_modified field