Nucleic Acids Research, 2010, Vol. 38, Web Server issue W135 Figure 2. Mapping results. (A) Table of results (B) Visualization of the identiﬁed metabolites in the metabolic network. (C) Extraction of the subnetwork linking the identiﬁed metabolites. The graphical representation of the entire metabolic network of an organism can be very dense (i.e. with many nodes and overlapping edges). Following reaction paths connecting identiﬁed metabolites can be diﬃcult within such an output. To improve visualization in such circumstances, we have developed a Cytoscape plug-in (GapFiller) to compute subnetworks of identiﬁed metab- olites (23) (Figure 2C). Finally, by creating a MetExplore account, users can create a history of all analyses allowing subsequent consultation without reprocessing. METABOLIC GRAPH ANALYSES In addition to oﬀering the potential to store and visualize data from metabolomics data sets within the context of a virtual metabolome, MetExplore provides several func- tions based on graph analysis that facilitate understanding of the role of metabolites within the network. For example, these methods can be used for drug target identiﬁcation (11) or to decipher the biosynthetic links between metabolites (24,12). Choke points One successful and practical use of global metabolic networks has been the introduction of choke point analysis. Choke points are deﬁned as reactions that either uniquely consume a speciﬁc substrate or uniquely produce a speciﬁc product (11). Choke point analysis, such as used for the malaria parasite Plasmodium falcip- arum has shown current drug targets are far more likely to be choke points within the network than other reactions (11). Furthermore, comparison between choke points in parasites and their hosts identiﬁes parasite-speciﬁc choke points as being even better candidate targets. Scope The scope of metabolites allows the identiﬁcation of the potential biosynthetic capacity of an organism from a