Analyzing the structural variability of macromolecules using advanced imaging techniques
Official title: Comprehensive analysis of macromolecule structural variability in CryoEM/CryoET
Funded at Stanford University · NIH-10932180 · Data updated 2026-11-12
This study is all about using special imaging techniques to take detailed pictures of proteins and other large molecules in different shapes, helping us learn how they work and change, which could improve our understanding of health and diseases.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project start | September 21, 2023 |
| Project end | July 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $365,956 |
| NIH project number | 5R01GM150905-02 |
| Project ID | NIH-10932180 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with conditions related to protein misfolding or structural abnormalities, such as certain genetic disorders or neurodegenerative diseases.
✕Less likely to help
Patients with conditions unrelated to protein structure or function may not receive any benefit from this research.
What this research studies
This research focuses on developing computational tools to analyze how macromolecules, such as proteins, vary in structure when imaged using Cryogenic electron microscopy (CryoEM) and Cryogenic electron tomography (CryoET). By capturing snapshots of these macromolecules in different states, the research aims to understand their dynamic interactions and structural flexibility, which are crucial for their functions. The project employs advanced algorithms, including Gaussian mixture models and deep neural networks, to refine and interpret the structural data, providing insights into the relationship between structure and function. This could lead to a better understanding of various biological processes and diseases.
Why it matters
Potential benefit: If successful, this research could enhance our understanding of protein behavior, potentially leading to improved treatments for diseases related to protein misfolding or dysfunction.
How similar studies have gone: Other research has shown success in using advanced imaging techniques and computational tools to analyze protein structures, indicating that this approach has a strong foundation.
Where this research is happening
-
Stanford University
Stanford, United States Active
Researchers
- Principal investigator: Chen, Muyuan — Stanford University
- Study coordinator: Chen, Muyuan
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.