Semi-Automated NMR Metabolite Identification via Machine Learning
EMSL Project ID
60468
Abstract
Current EMSL metabolomics capabilities enable automated Nuclear Magnetic Resonance (NMR) data acquisition, yet downstream processing of these data is manually intensive and time-consuming. The largest bottlenecks among these downstream processes are feature (metabolite) identification and quantification; these two steps typically require an experienced analyst several hours to complete for a single sample. An open-source R package, nmRanalysis, and user interface (UI) are currently under development (EMSL Proposal 60117) for semi-automated metabolite quantification. We propose to further develop the R package and UI to streamline and increase the efficiency of metabolite identification for NMR data, thereby addressing the two main bottlenecks in NMR metabolomics analyses and expanding the capabilities of nmRanalysis.
Project Details
Start Date
2022-10-01
End Date
2024-01-31
Status
Closed
Released Data Link
Team
Principal Investigator
Co-Investigator(s)
Team Members