MetDraftBuilder: a tool for automatic metabolic network reconstruction

Metabolism is the organism’s machinery that breaks down complex organic molecules to produce the energy and building blocks needed for the organism’s normal functioning. It comprises all chemical and physical processes that occur within the cells of living organisms and that allow for maintaining life. Recent research studies and tools are focused on approaches to reconstruct the metabolism of a species (or a group of species) starting from experimental (genomic) data. In fact, such activity is very complex and time consuming, but can be partially automated thanks to the use of tools and pipelines that make use of the knowledge stored in metabolic databases. In this thesis, we propose a tool, MetDraftBuilder, to automatically build a draft metabolic network out of the experimental data given in input, pre-processed as a homogeneous list of either KEGG Orthology (KO) or reaction function (RN) identifiers. The tool relies on the knowledge stored in the KEGG database and on the way metabolic data are organized. The resulting draft metabolism only includes qualitative information, such as the active metabolic pathways, genes, relations and chemical reactions. This information, however, is sufficient to recover the topology of the resulting metabolic network, which can be used for analysis and comparison purposes.