Metabolomics

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CASMDB: An Open-Source Database of Metabolite Annotation Data for 1D 1 H NMR-Based Metabolomics


ABSTRACT: In metabolomics analyses, databases are invaluable for the identification of individual metabolites in experimentally collected samples. Publicly available databases for NMR-based metabolomics are unfortunately incomplete with respect to experimental conditions, such as pH, temperature, and NMR field strength, which all affect the observed signals. Moreover, derived NMR annotation parameters, such as peak positions and multiplet patterns, are also often incomplete and contain crucial errors. Hence, these databases are often inadequate for the analyses of experimental samples across a range of conditions, most notably field strength. In this paper, we describe the collection, remediation, and integration of annotation data from the publicly available HMDB, BRMB, and GISSMO NMR metabolomics databases to build the CcpNmr Analysis Simulated Metabolomics Database (CASMDB). CASMDB contains 1932 unique and fully annotated metabolite entries that allow for accurate simulation of spectra at arbitrary field strengths. CASMDB can be downloaded as a standalone, versioned repository from GitHub and easily augmented with new entries. CASMDB underpins the visualizing of experimental and simulated metabolite references and allows for 1D 1H NMR-based metabolomics studies.

INSTRUMENT(S): Nuclear Magnetic Resonance (NMR) -

PROVIDER: MTBLS6263 | MetaboLights | 2026-04-21

REPOSITORIES: MetaboLights

Dataset's files

Source:
Action DRS
a_MTBLS6263_NMR___metabolite_profiling.txt Txt
i_Investigation.txt Txt
m_MTBLS6263_NMR___metabolite_profiling_v2_maf.tsv Tabular
s_MTBLS6263.txt Txt
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Publications

CASMDB: An Open-Source Database of Metabolite Annotation Data for 1D <sup>1</sup>H NMR-Based Metabolomics.

Hayward Morgan W MW   Mureddu Luca G LG   Thompson Gary S GS   Phelan Marie M MM   Brooksbank Edward J EJ   Vuister Geerten W GW  

Analytical chemistry 20260421 17


In metabolomics analyses, databases are invaluable for the identification of individual metabolites in experimentally collected samples. Publicly available databases for NMR-based metabolomics are unfortunately incomplete with respect to experimental conditions, such as pH, temperature, and NMR field strength, which all affect the observed signals. Moreover, derived NMR annotation parameters, such as peak positions and multiplet patterns, are also often incomplete and contain crucial errors. Hen  ...[more]

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