A web tool for predicting RNA structures using evolutionary data
Official title: An all-in-one web server for RNA structure prediction using evolutionary information
Funded at Harvard University · NIH-10757425 · Data updated 2026-11-12
This study is creating an easy-to-use online tool that helps scientists predict how RNA molecules are shaped by looking at information from different living things, making it better for understanding how RNA works in our bodies.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Harvard University NIH-funded |
| Lab location | 1 site (Cambridge, United States) |
| Project start | January 1, 2023 |
| Project end | December 31, 2025 |
| Funding year | 2024 |
| Award (this year) | $164,711 |
| NIH project number | 5R21GM148902-02 |
| Project ID | NIH-10757425 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for benefiting from this research include individuals with genetic disorders or diseases where RNA plays a critical role in disease mechanisms.
✕Less likely to help
Patients with conditions unrelated to RNA structure or function may not receive any benefit from this research.
What this research studies
This research focuses on developing a user-friendly web server that predicts RNA structures by analyzing evolutionary information from various organisms. It aims to improve the accuracy of RNA structure predictions, which are crucial for understanding RNA function in biological processes. The tool will utilize advanced computational methods to evaluate RNA sequences and propose the most likely biological structures. By making this tool freely available, it seeks to enhance accessibility for researchers and clinicians alike.
Why it matters
Potential benefit: If successful, this research could provide a reliable method for predicting RNA structures, leading to better understanding and treatment of diseases linked to RNA dysfunction.
How similar studies have gone: Previous research has shown success in using evolutionary information for protein structure prediction, indicating a promising potential for similar approaches in RNA structure prediction.
Where this research is happening
-
Harvard University
Cambridge, United States Active
Researchers
- Principal investigator: Rivas, Elena — Harvard University
- Study coordinator: Rivas, Elena
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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.