Creating a standardized database for metabolomics data processing
Official title: A reproducible database for untargeted metabolomics data processing across laboratories
Funded at University of California at Davis · NIH-10939147 · Data updated 2026-11-12
This study is creating a helpful online tool that will make it easier for scientists to share and understand data about tiny molecules in our bodies, which can lead to better insights into health and diseases.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California at Davis NIH-funded |
| Lab location | 1 site (Davis, United States) |
| Project start | September 15, 2024 |
| Project end | July 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $532,947 |
| NIH project number | 1R01GM155383-01 |
| Project ID | NIH-10939147 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for benefiting from this research include individuals with conditions that can be studied through metabolomics, such as metabolic disorders or chronic diseases.
✕Less likely to help
Patients with conditions that are not related to metabolomics or those who do not have access to participating laboratories may not benefit from this research.
What this research studies
This research aims to develop a cloud-based database called LC-BinBase that will standardize the processing of metabolomics data across different laboratories. By using high-resolution mass spectrometry techniques, the project will ensure that data from various sources can be harmonized, allowing for more reliable and reproducible results. The research involves creating algorithms that will provide confidence scores for metabolite identification, enhancing the interpretability of the data for biomedical researchers. Ultimately, this project seeks to improve the quality of metabolomics data, making it more accessible and useful for various applications in health and disease.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and consistent metabolomics data, which can enhance the understanding of diseases and improve patient care.
How similar studies have gone: Previous research has shown success in standardizing data processing in other fields, suggesting that this approach could be effective in metabolomics as well.
Where this research is happening
-
University of California at Davis
Davis, United States Active
Researchers
- Principal investigator: Fiehn, Oliver — University of California at Davis
- Study coordinator: Fiehn, Oliver
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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.