Content
Knowledge about the metabolic capacity of an organism can be intuitively represented as a network of compounds, connected by the biochemical reactions that consume and produce them, i.e. a Genome-Scale Metabolic Networks (GSMN). The structure of this network can provide valuable information for interpreting metabolomic results, by putting them in the context of the whole system they're part of. This session is aimed for a gentle introduction to network science and graph theory, presenting concepts and analysis most relevant to the metabolomician. It will highlight the common pitfalls and challenges specific to the application to GSMN. A practical session will be dedicated to the information extraction and visual exploration of metabolic networks in MetExplore, and the use of MetaboRank to find new metabolite candidates to investigate.
Goals and learning points
1.1) Understanding GSMN: how they are built, their use and their limitations
1.2) Understanding the basic concepts behind network science
1.3) Interpreting distances and topological measures in metabolic network
2.1) How to browse information about metabolism in MetExplore
2.2) How to map metabolomics data onto a metabolic network in MetExplore
2.3) How to visualise and explore networks with MetExploreViz
2.4) How to go beyond a signature using MetaboRank recommender system
Format
The session will start by a theoretical lecture on biological network analysis focused on metabolomic results interpretation. It will be followed by a brief review of existing tools for network analysis, and a hands-on session on MetExplore, a web server dedicated to the analysis and visualisation of GSMN.