Improving peptide identification from mass spectrometry data using machine learning
Official title: Machine-Learning Models for big data omics
Funded at Florida International University · NIH-11117126 · Data updated 2026-11-12
This study is working on better ways to find important proteins in your body using advanced computer techniques, which could help doctors understand health issues and discover new clues about diseases that affect you.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Florida International University NIH-funded |
| Lab location | 1 site (Miami, United States) |
| Project start | June 15, 2024 |
| Project end | May 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $347,973 |
| NIH project number | 5R35GM153434-02 |
| Project ID | NIH-11117126 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with conditions that may be linked to overlooked proteins or biomarkers in their biological data.
✕Less likely to help
Patients who do not have conditions related to the proteins being studied or who are not involved in mass spectrometry analyses may not benefit from this research.
What this research studies
This research focuses on enhancing the identification of peptides from mass spectrometry (MS) data, which is crucial for understanding human health and disease. Current methods often overlook important, less abundant proteins, leading to wasted data and incomplete analyses. By developing advanced machine-learning models, the project aims to create more accurate and reliable methods for analyzing complex biological data. Patients may benefit from improved understanding of biomarkers related to various health conditions as a result of this research.
Why it matters
Potential benefit: If successful, this research could lead to better identification of biomarkers for diseases, improving diagnosis and treatment options for patients.
How similar studies have gone: Other research has shown promise in using machine learning for data analysis in biological contexts, indicating that this approach could yield significant advancements.
Where this research is happening
-
Florida International University
Miami, United States Active
Researchers
- Principal investigator: Saeed, Fahad — Florida International University
- Study coordinator: Saeed, Fahad
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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.