Understanding how alternative splicing changes RNA-binding proteins in autoimmune diseases
Official title: Unraveling the Impact of Alternative Splicing on RNA-Binding Protein Function Using Integrative Machine Learning
Funded at Worcester Polytechnic Institute · NIH-11344237 · Data updated 2026-11-12
A scientist at a U.S. university is using advanced computer methods and lab tests to see how different versions of RNA-binding proteins, created by alternative splicing, might affect autoimmune diseases.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Worcester Polytechnic Institute NIH-funded |
| Lab location | 1 site (Worcester, United States) |
| Project start | August 10, 2026 |
| Project end | April 30, 2030 |
| Funding year | 2026 |
| Award (this year) | $431,535 |
| NIH project number | 1R01GM164526-01 |
| Project ID | NIH-11344237 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with autoimmune diseases whose condition may be affected by RNA-binding protein function or splicing could be eligible for future translational work.
✕Less likely to help
Individuals without autoimmune diseases are unlikely to gain direct benefit from this specific mechanistic study.
What this research studies
This project will merge transcriptome, proteome, interaction, and structure data with cutting-edge machine learning to study how alternative splicing changes RNA-binding proteins and their roles in cells. Researchers will predict which protein variants are stable and functionally important, then test these predictions in lab experiments focusing on medically relevant RBPs. The work aims to map how spliced isoforms influence RNA metabolism and cellular homeostasis, potentially revealing new angles for therapy. By linking computational predictions with experimental validation, the project seeks to identify isoforms that could contribute to disease processes or serve as therapeutic targets.
Why it matters
Potential benefit: If successful, patients with autoimmune diseases could benefit from new targets or strategies stemming from a better understanding of how RNA-binding protein variants influence disease mechanisms.
How similar studies have gone: Previous work shows that integrating multi-omic data with machine learning can reveal functionally important protein isoforms, supporting potential impact.
Where this research is happening
-
Worcester Polytechnic Institute
Worcester, United States Active
Researchers
- Principal investigator: Korkin, Dmitry — Worcester Polytechnic Institute
- Study coordinator: Korkin, Dmitry
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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.