Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Designing and Operating an In-House Cryogenic Electron Microscopy Facility with IT Infrastructure and On-the-Fly Data Processing Pipelines. |
| Συγγραφείς: |
Shell E; ITS-Technology Engineering, Information Technology Services, Physical & Biological Sciences Division, University of California-Santa Cruz.; Biomolecular Cryo-Electron Microscopy Facility, University of California-Santa Cruz., Balasco Serrão VH; Biomolecular Cryo-Electron Microscopy Facility, University of California-Santa Cruz.; Chemistry and Biochemistry Department, University of California-Santa Cruz; vbalasco@ucsc.edu. |
| Πηγή: |
Journal of visualized experiments : JoVE [J Vis Exp] 2026 Sep 01 (235). Date of Electronic Publication: 2026 Sep 01. |
| Τύπος έκδοσης: |
Journal Article; Video-Audio Media |
| Γλώσσα: |
English |
| Στοιχεία περιοδικού: |
Publisher: MYJoVE Corporation Country of Publication: United States NLM ID: 101313252 Publication Model: Electronic Cited Medium: Internet ISSN: 1940-087X (Electronic) Linking ISSN: 1940087X NLM ISO Abbreviation: J Vis Exp Subsets: MEDLINE |
| Imprint Name(s): |
Original Publication: [Boston, Mass. : MYJoVE Corporation, 2006]- |
| Ιατρικοί όροι (MeSH): |
Cryoelectron Microscopy*/instrumentation , Cryoelectron Microscopy*/methods |
| Περίληψη: |
Cryo-EM has become a dominant method for high-resolution structural determination of biological macromolecules. As the number of institutional cryo-EM facilities grows worldwide, a persistent challenge has emerged: the data infrastructure required to support these facilities is routinely underplanned. Modern cryo-EM instruments paired with direct electron detectors (DEDs) generate between 2 and 5 TB of raw data per day, and a 20-user facility can accumulate approximately 2 PB of data within a single operational year. Processing this data demands dedicated GPU computing nodes, high-speed internal networking, and robust long-term archival strategies-all of which must be in place before data collection begins. This protocol presents an integrated framework for the IT and computational design of an in-house cryo-EM facility. We cover physical facility requirements (room design, power, cooling, and vibration isolation), equipment selection (microscopes, DEDs, and supporting instruments), and the full computational stack: network switch configuration, storage server selection and sizing, GPU compute node provisioning, and remote access architecture. We then provide a detailed protocol for implementing on-the-fly data processing pipelines-covering motion correction, contrast transfer function (CTF) estimation, particle picking, and 2D classification in real time during data collection-using industry-standard tools. Data transfer strategies for external users are also addressed. This guide fills a critical gap in the literature and will enable researchers and administrators to build cryo-EM facilities that are computationally ready from day one. |
| Entry Date(s): |
Date Created: 20260902 Date Completed: 20260902 Latest Revision: 20260909 |
| Update Code: |
20260909 |
| DOI: |
10.3791/71837 |
| PMID: |
42683890 |
| Βάση Δεδομένων: |
MEDLINE |