Improving Isotope Ratio Accuracy in Metabolic Labeling Using Orbitrap Mass Spectrometry: A Machine Learning Correction Algorithm for Metabolic Flux Analysis
To develop a machine learning algorithm that improves accuracy in isotope ratio measurement for metabolic flux analysis.
Utilized Orbitrap mass spectrometry for isotope ratio analysis
Developed and implemented a machine learning correction algorithm
Focused on enhancing high-throughput capabilities in labeling experiments.
Achieved improved accuracy in isotope ratio measurements
Enabled stable isotope labeling experiments to function at high-throughput
Potentially advanced techniques in untargeted fluxomics.
Abstract
range. The approach presented here enables stable isotope labeling experiments to be high-throughput and may advance stable isotope labeling toward untargeted "fluxomics".