  In many key applications of metabolomics, such as toxicology or
nutrigenomics, it is of interest to profile and detect changes in metabolic
processes, usually represented in the form of pathways. As an alternative, a
broader point of view would enable investigators to better understand the
relations between entities that exist in different processes. Therefore,
relating a possible perturbation to several known processes represents a new
approach to this field of study. We propose to use a network representation of
metabolism in terms of reactants, enzyme and metabolite. To model these systems
it is possible to describe both reactions and relations among enzymes and
metabolites. In this way, analysis of the impact of changes in some metabolites
or enzymes on different processes are easier to understand, detect and predict.
Results: We release the MetaboX library, an open source PHP framework for
developing metabolic networks from a set of compounds. This library uses data
stored in Kyoto Encyclopedia for Genes and Genomes (KEGG) database using its
RESTful Application Programming Interfaces (APIs), and methods to enhance
manipulation of the information returned from KEGG webservice. The MetaboX
library includes methods to extract information about a resource of interest
(e.g. metabolite, reaction and enzyme) and to build reactants networks,
bipartite enzyme-metabolite and unipartite enzyme networks. These networks can
be exported in different formats for data visualization with standard tools. As
a case study, the networks built from a subset of the Glycolysis pathway are
described and discussed. Conclusions: The advantages of using such a library
imply the ability to model complex systems with few starting information
represented by a collection of metabolites KEGG IDs.
