NCCAT Cross-training Programs2019-11-26T20:50:11+00:00
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US States, Districts & Territories
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Annual calls for cross-training proposals
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Year TP Program Established

THE NCCAT EXPERIENCE

We believe no two trainees are alike. We take the time to get to know you so we can help you learn how to incorporate cryoEM into your biomedical research toolkit.

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Embedded Cross-training Modules

Objectives:
Learn about different parameters during grid preparation that affect sample quality and ice thickness.

Milestones:
• Reproducible sample preparation of a test sample with the Vitrobot Mark IV, Leica GP, and/or CP3.
• Identify sample preparation conditions for an applicant’s driving biological project and to prepare grids reproducibly.

Objectives:
Learn about the operation of screening microscopes and Krios microscopes. Learn which alignments are important for obtaining high-quality data on an EM, how to check if it is aligned correctly and how to do the alignments.

Milestones:
• Check the alignments on an EM and be able to adjust them if necessary.
• Know the most common errors occurring on an EM during operation and how to deal with them.

Objectives:
Learn to assess if a sample is ready for data collection, what to check on the microscope before starting a long data collection, and how to operate the Leginon acquisition software. Furthermore, judging how many micrographs would be necessary for a reasonably good structure by looking at the micrographs and pre-processed data.

Milestones:
• Set up a data collection from a test sample and obtain enough data to get a high-resolution structure.
• Determine data acquisition parameters for applicant’s sample and collect enough data for an initial 3D model.

Objectives:
Learn how to use on-the-fly processing through Appion to optimize a data collection experiment in real time. After data collection is complete learn to process data with commonly used software packages and pipelines (RELION3 and cryoSPARC) from motion correction to 3D model refinement.

Milestones:
• Obtain a high-resolution structure from a test data set with commonly used software packages.
• Process a data set from the applicant’s own sample and obtain a 3D model.

Core Cross-training Components