W132–W137 Nucleic Acids Research, 2010, Vol. 38, Web Server issue doi:10.1093/nar/gkq312 Published online 5 May 2010 MetExplore: a web server to link metabolomic experiments and genome-scale metabolic networks Ludovic Cottret1,*, David Wildridge 2 , Florence Vinson 1 , Michael P. Barrett2, Hubert Charles3,4, Marie-France Sagot3,5 and Fabien Jourdan1 1INRA, UMR1089, Xe´ nobiotiques, F-31000 Toulouse, France, 2Division of Infection and Immunity, Glasgow Biomedical Research Centre, University of Glasgow, Glasgow, UK, 3Bamboo Team, INRIA Grenoble-Rhoˆ ne-Alpes, 38330 Montbonnot Saint-Martin, 4UMR203 Biologie Fonctionnelle Insectes et Interactions (BF2I), INRA, INSA-Lyon, Universite´ de Lyon, F-69621 Villeurbanne and 5Universite´ de Lyon, F-69000, Lyon; Universite´ Lyon 1; CNRS, UMR5558, Laboratoire de Biome´ trie et Biologie Evolutive, F-69622, Villeurbanne, France Received January 29, 2010; Revised March 30, 2010; Accepted April 17, 2010 ABSTRACT High-throughput metabolomic experiments aim at identifying and ultimately quantifying all metabolites present in biological systems. The metabolites are interconnected through metabolic reactions, gener- ally 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 con- nectivity 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 con- sidered 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 meta- bolic network of an organism, then applying graph-based methods and advanced visual- ization tools to enhance data analysis. The MetExplore web server is freely accessible at http://metexplore.toulouse.inra.fr. INTRODUCTION Metabolomics aims at identifying the metabolome, i.e. the full set of metabolites present in a biological system (1). Cellular metabolite concentrations are ultimately a reﬂec- tion of cell function (i.e. gene expression regulation and protein interactions). They are modulated by genetic or environmental perturbations and thus can be considered as central to the phenotype of an organism. These metab- olites are the inputs and outputs of biochemical reactions organized into the complex system commonly termed the metabolic network. To date, techniques that allow the quantitative measurement of all metabolites within a given system are not available and this confounds systems level analysis of output from metabolomics ex- periments. Methods that permit meaningful connections to be inferred between metabolites thus oﬀer the potential to enhance metabolite analysis from the network perspective. The availability of complete genome sequences has allowed the construction of predicted metabolic networks for many organisms by using information on the presence of enzymes inferred from the presence of the genes that encode them and reference to known bio- chemical pathways whose structure was determined through the methods of classical biochemistry (2,3). The main metabolic databases such as KEGG (4) or BioCyc (5) are built on this pathway-oriented model. In metabolomics, these databases are used for the analysis of metabolites in the context of global metabolism. The MassTRIX web server (6), for example, shows candidate metabolites as coloured objects on the KEGG pathway maps (7). If the positive identiﬁcation of metabolites has already been made, tools such as the Omics Viewer of BioCyc (8) or the pathway projector (9) allow metabolites to be highlighted on a collection of organism-speciﬁc metabolic maps. However, in such models, the same metabolite is duplicated if it is involved in multiple metabolic pathways. Moreover, some paths linking identiﬁed *To whom correspondence should be addressed. Tel: +33 561285720; Fax: +33 561285244; Email: ludovic.cottret@toulouse.inra.fr The Author(s) 2010. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.