# cryoEDU: An online curriculum and software platform for hands-on learning in single-particle cryoEM and cryoET

> **NIH NIH R25** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $118,802

## Abstract

cryoEDU: An online curriculum and software platform for hands-on learning in single-
particle cryoEM and cryoET
SUMMARY
Single-particle cryogenic electron microscopy (cryoEM) has become a mainstream structural biology technique
due to reduced burden of sample preparation, the capacity to solve integral membrane protein complex
structures, and the ability to visualize large structurally heterogeneous macromolecular complexes at high
resolution. As cryoEM expands, the nascent field of cryogenic electron tomography (cryoET) continues to
achieve milestones – such as structure determination in situ – indicating that cryoET will soon become a core
technology for structural and cell biologists for both in vitro and in vivo structural characterizations. In both
cryoEM and cryoET, new users face a significant educational barrier: practitioners must understand concepts
that range from biochemistry to physics of electron microscopes to computational image alignment algorithms.
Although there are cryoEM workshops currently available address these concepts with hands-on training, the
limited capacity and intimate format results in substantial oversubscription and an inability to train new cryoEM
users en masse. As such, there exists a significant gap in training materials and resources that help users
understand, analyze, interpret, and validate cryoEM data and structure determination. Towards this end, we
propose to build an online educational platform focused on cryoEM/ET data processing called ‘cryoEDU’. The
cryoEDU platform is built on three pillars: 1) self-paced online modular curricula; 2) hands-on data analysis
in a cloud desktop environment; and 3) community engagement to facilitate information exchange related
to cryoEM/ET data analysis. Online educational curricula will incorporate real cryoEM/ET data into learning
modules on specific topics in addition to evaluations that highlight best practices and common pitfalls to help
train learners in rigor for cryoEM/ET analysis. To ensure adequate data analysis training, we will allow users to
submit simulated jobs and interact with cryoEM software using a cloud desktop environment. Importantly, users
will not be running real time algorithms, but instead, we will pull results from a precalculated results database
containing nearly all conceivable outcomes. The cloud desktop will enable users to make parameter choices and
receive immediate results feedback, creating a new paradigm in cryoEM/ET data analysis learning. Finally, we
will engage with the cryoEM/ET community by including testimonials on our website, highlighting decisions made
by experts when analyzing data, and recording live conversations with primary authors on important cryoEM/ET
publications. We recognize that cryoEM and cryoET continue to grow at a fast pace, which is why we expect our
content to evolve with changes in the field and with user feedback via learning assessment and surveys. We
believe that the cryoEDU platform will facilitate...

## Key facts

- **NIH application ID:** 10436923
- **Project number:** 5R25EY032739-02
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Michael Cianfrocco
- **Activity code:** R25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $118,802
- **Award type:** 5
- **Project period:** 2021-07-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10436923

## Citation

> US National Institutes of Health, RePORTER application 10436923, cryoEDU: An online curriculum and software platform for hands-on learning in single-particle cryoEM and cryoET (5R25EY032739-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10436923. Licensed CC0.

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