Development of a Pipeline for Automated Reconstruction and Annotation of Data Independent Acquisition LC-MS Datasets
Gonçalo Graça, Yuheng Cai, Elizabeth J. Want, Timothy M. D. Ebbels Division of Integrative Systems Medicine and Digestive Disease, Faculty of Medicine, Imperial College London, UK
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Gonçalo Graça (Presenter) Imperial College London
Presenter Bio: I obtained a BSc in Biochemistry in 2005 (University of Lisbon, Portugal) and a PhD in Chemistry (University of Aveiro, Portugal). I've been working in Metabolomics since 2005, particularly in the application of NMR, LC-MS and Infra-red spectroscopy in disease diagnostics. I'm currently a Postdoctoral Research Associate at Imperial College London. My work consists in the annotation of metabolite features from untargeted metabolic profiling NMR and LC-MS datasets obtained in human epidemiological studies.
Relevant Financial Disclosures
(within past 24 months, reported on Sep 13, 2021)
No relevant financial relationship(s) to disclose.
Abstract
Reconstruction of parent-fragment ion relationships from data independent acquisition (DIA) remains a challenge in non-targeted MS metabolomics and lipidomics analysis. In the presented work we propose a novel strategy to improve the reconstruction of DIA fragmentation MSE data in order to automatically annotate the majority of known metabolites/lipids in human serum.
= Discovery stage.
= Translation stage.
= Clinically available.
