4.4 Article

Using Scipion for stream image processing at Cryo-EM facilities

期刊

JOURNAL OF STRUCTURAL BIOLOGY
卷 204, 期 3, 页码 457-463

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jsb.2018.10.001

关键词

Electron microscopy; Streaming Image processing; Live processing; High throughput; Scipion

资金

  1. Spanish Ministry of Economy and Competitiveness [BIO2016-76400-R]
  2. AEI/FEDER [BFU 2016 74868P]
  3. Comunidad Autonoma de Madrid [S2017/BMD-3817]
  4. European Union (EU) and Horizon 2020 through grant Corbel [INFRADEV-1-2014-1, 654248]
  5. Science for Life Laboratory
  6. European Union (EU) and Horizon 2020 through grant EOSCpilot [INFRADEV-04-2016, 739563]
  7. EGI-Engage project (Horizon 2020) [654142]
  8. European Union (EU) and Horizon 2020 through grant West-Life [EINFRA-2015-1, 675858]
  9. European Union (EU) and Horizon 2020 through grant iNEXT [INFRAIA-1-2014-2015, 653706, 676559]
  10. Knut and Alice Wallenberg
  11. Family Erling Persson Foundation
  12. Kempe Foundation
  13. SciLifeLab, Stockholm University
  14. UmeA University
  15. Wellcome Trust
  16. MRC
  17. BBSRC
  18. MRC [MC_UP_A025_1011] Funding Source: UKRI

向作者/读者索取更多资源

Three dimensional electron microscopy is becoming a very data-intensive field in which vast amounts of experimental images are acquired at high speed. To manage such large-scale projects, we had previously developed a modular workflow system called Scipion (de la Rosa-Trevfn et al., 2016). We present here a major extension of Scipion that allows processing of EM images while the data is being acquired. This approach helps to detect problems at early stages, saves computing time and provides users with a detailed evaluation of the data quality before the acquisition is finished. At present, Scipion has been deployed and is in production mode in seven Cryo-EM facilities throughout the world.

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