Use of reconstituted metabolic networks to assist in metabolomic data visualization and mining

Fabien Jourdan*, Ludovic Cottret, Laurence Huc, David Wildridge, Richard Scheltema, Anne Hillenweck, Michael P. Barrett, Daniel Zalko, David G. Watson, Laurent Debrauwer

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    27 Citations (Scopus)
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    Metabolomics experiments seldom achieve their aim of comprehensively covering the entire metabolome. However, important information can be gleaned even from sparse datasets, which can be facilitated by placing the results within the context of known metabolic networks. Here we present a method that allows the automatic assignment of identified metabolites to positions within known metabolic networks, and, furthermore, allows automated extraction of sub-networks of biological significance. This latter feature is possible by use of a gap-filling algorithm. The utility of the algorithm in reconstructing and mining of metabolomics data is shown on two independent datasets generated with LC-MS LTQ-Orbitrap mass spectrometry. Biologically relevant metabolic sub-networks were extracted from both datasets. Moreover, a number of metabolites, whose presence eluded automatic selection within mass spectra, could be identified retrospectively by virtue of their inferred presence through gap filling.

    Original languageEnglish
    Pages (from-to)312-321
    Number of pages10
    Issue number2
    Publication statusPublished - Jun-2010


    • Metabolic network
    • Graph algorithm
    • Gap-filling
    • Metabolomics
    • GENOME
    • TOOL

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