Using deep learning to improve how we reconstruct protein structures from cryo-EM images
Deep learning methods for automated and accurate reconstruction of protein structures from cryo-EM image data
This study is working on improving how scientists create 3D models of proteins from special images, which could help develop better treatments and drugs for patients in the future.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Missouri-Columbia NIH-funded |
| Lab location | 1 site (Columbia, United States) |
| Project ID | NIH-11089486 on NIH RePORTER |
What this research studies
This research focuses on enhancing the accuracy and efficiency of reconstructing protein structures using cryogenic electron microscopy (cryo-EM) images. By developing advanced deep learning methods, the project aims to automate the process of identifying and building protein structures from complex image data. This approach leverages large datasets of high-resolution cryo-EM images and employs innovative neural network architectures to overcome current limitations in the field. Patients may benefit indirectly through advancements in understanding protein structures, which can lead to better-targeted therapies and drug designs.
Who could benefit from this research
Good fit: Ideal candidates for benefiting from this research include individuals with conditions related to protein misfolding or dysfunction, such as certain genetic disorders or neurodegenerative diseases.
Not a fit: Patients with conditions unrelated to protein structures or those not affected by protein misfolding may not receive direct benefits from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and efficient methods for determining protein structures, ultimately improving drug development and treatment strategies for various diseases.
How similar studies have performed: Other research has shown success in using deep learning techniques for image processing and protein structure determination, indicating a promising direction for this approach.
Where this research is happening
Columbia, United States
- University of Missouri-Columbia — Columbia, United States (Active)
Researchers
- Principal investigator: Cheng, Jianlin — University of Missouri-Columbia
- Study coordinator: Cheng, Jianlin
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 below.