Publications by authors named "Madelyn R Shapiro"
Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence─the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies.
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- High-resolution mass spectrometry data can be better understood through orthogonal separations, helping to more accurately annotate molecules in untargeted metabolomics.
- Molecular networks (MNs) serve as a key tool for visualizing relationships between molecular data, improving the annotation process using mathematical graphs.
- The introduction of molecular hypernetworks (MHNs) offers a more advanced model for representing complex relationships among data, enhancing exploratory analysis and annotation confidence compared to traditional MNs.
Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence - the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies.
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