Developing methods to understand how genes are spliced in health and disease
Official title: Computational Methods to Characterize Alternative Splicing and Genetic Determinants from Heterogeneous Sequence Data
Funded at Johns Hopkins University · NIH-11011545 · Data updated 2026-11-12
This study is working on new tools to better understand how changes in gene expression might be linked to different diseases, which could help patients learn more about their genetic conditions.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Johns Hopkins University NIH-funded |
| Lab location | 1 site (Baltimore, United States) |
| Project start | January 1, 2025 |
| Project end | November 30, 2029 |
| Funding year | 2025 |
| Award (this year) | $363,392 |
| NIH project number | 1R35GM156374-01 |
| Project ID | NIH-11011545 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals with genetic disorders or diseases where alternative splicing plays a significant role.
✕Less likely to help
Patients without genetic conditions or those not affected by alternative splicing may not benefit from this research.
What this research studies
This research focuses on creating advanced computational tools to analyze alternative splicing, a process that affects how genes are expressed in the body. By utilizing cutting-edge sequencing technologies, the project aims to identify variations in splicing that may contribute to various diseases. The approach involves analyzing large datasets from diverse patient populations to uncover genetic factors that influence splicing. Patients may benefit from improved understanding of their genetic conditions through these innovative methods.
Why it matters
Potential benefit: If successful, this research could lead to better diagnostic tools and targeted therapies for diseases linked to alternative splicing.
How similar studies have gone: Previous research has shown promise in using computational methods to analyze genetic data, indicating potential for success in this novel approach.
Where this research is happening
-
Johns Hopkins University
Baltimore, United States Active
Researchers
- Principal investigator: Florea, Liliana D — Johns Hopkins University
- Study coordinator: Florea, Liliana D
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.