Journal
NUCLEIC ACIDS RESEARCH
Volume 38, Issue -, Pages W132-W137Publisher
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkq312
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Funding
- ANR [REGLIS NT05-3_45205, MIRI BLAN08-1335497]
- ANR-BBSRC [ANR-BBSRC MetNet4SysBio ANR-07-BSYS 003 02, ANR-BBSRC SysTryp]
- University of Glasgow
- Biotechnology and Biological Sciences Research Council [BB/I004599/1, BB/F005679/1] Funding Source: researchfish
- BBSRC [BB/I004599/1, BB/F005679/1] Funding Source: UKRI
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High-throughput metabolomic experiments aim at identifying and ultimately quantifying all metabolites present in biological systems. The metabolites are interconnected through metabolic reactions, generally grouped into metabolic pathways. Classical metabolic maps provide a relational context to help interpret metabolomics experiments and a wide range of tools have been developed to help place metabolites within metabolic pathways. However, the representation of metabolites within separate disconnected pathways overlooks most of the connectivity of the metabolome. By definition, reference pathways cannot integrate novel pathways nor show relationships between metabolites that may be linked by common neighbours without being considered as joint members of a classical biochemical pathway. MetExplore is a web server that offers the possibility to link metabolites identified in untargeted metabolomics experiments within the context of genome-scale reconstructed metabolic networks. The analysis pipeline comprises mapping metabolomics data onto the specific metabolic network of an organism, then applying graph-based methods and advanced visualization tools to enhance data analysis. The MetExplore web server is freely accessible at http://metexplore.toulouse.inra.fr.
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