2011
DOI: 10.1186/1471-2105-12-400
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MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixtures

Abstract: BackgroundOne-dimensional 1H-NMR spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, the accurate identification of individual compounds is still a challenging task, particularly in spectral regions with higher peak densities. The need for automatic tools to facilitate and further improve the accuracy of such tasks, while using increasingly larger reference spectral libraries becomes a priority of current metabolomics research.ResultsWe intro… Show more

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Cited by 100 publications
(74 citation statements)
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“…The peaks were annotated through the HMDB49 and Metabohunter50 and targeted profiling51 was accomplished using ChenomX NMR Suite Profiler (version 7.7, ChenomX Inc.). The concentrations were referenced to a TMSP concentration of 0.5 mM.…”
Section: Methodsmentioning
confidence: 99%
“…The peaks were annotated through the HMDB49 and Metabohunter50 and targeted profiling51 was accomplished using ChenomX NMR Suite Profiler (version 7.7, ChenomX Inc.). The concentrations were referenced to a TMSP concentration of 0.5 mM.…”
Section: Methodsmentioning
confidence: 99%
“…There are a number of software packages that have emerged recently for the automated or semi-automated quantification of metabolites in NMR spectra. Examples of non-commercial packages include MetaboHunter [32], MetaboMiner [33], BQuant [34] and BATMAN [35]. This targeted approach is useful if a hypothesis on a certain family of metabolites is the main research objective of the study.…”
Section: Binningmentioning
confidence: 98%
“…NMR spectroscopy is one of the most widely used methods for analytical measurement of metabolic profiles due its (1) reliability, (2) reproducibility and (3) speed (Tulpan et al 2011). NMR has been applied to metabolite-profiling studies in areas as diverse as plant metabolism (Want et al 2005) human tissues extracts, body fluids (Beckonert et al 2007) and microbial metabolite (Tulpan et al 2011).…”
Section: C)mentioning
confidence: 99%