@inbook{2e4667e0c3a341a2b9df58a065796e3c,
title = "High accurate mass gas chromatography–mass spectrometry for performing isotopic ratio outlier analysis: Applications for nonannotated metabolite detection",
abstract = "Identification of unknown metabolites is one of the major issues for untargeted metabolomics studies. Isotopic ratio outlier analysis (IROA) technique uses specially designed isotopic patterns to reveal the carbon number of each metabolite and distinguish the biological originated metabolites from artifacts. This chapter describes the procedure to utilize the IROA technique with high accurate mass GC-MS to identify unknown metabolites.",
keywords = "High accurate mass GC-MS, Isotopic ratio outlier analysis, Metabolite identification, Metabolomics, Yeast",
author = "Yunping Qiu and Kurland, {Irwin J.}",
note = "Funding Information: This work was supported by the Stable Isotope and Metabolomics Core Facility of the Diabetes Research and Training Center (DRTC) of the Albert Einstein College of Medicine (NIH P60DK020541). Publisher Copyright: {\textcopyright} Springer Science+Business Media, LLC, part of Springer Nature 2021.",
year = "2021",
doi = "10.1007/978-1-0716-0864-7_7",
language = "English (US)",
series = "Neuromethods",
publisher = "Humana Press Inc.",
pages = "77--88",
booktitle = "Neuromethods",
}
