The document summarizes Dmitry Grapov's presentation on connecting metabolomic data with context. It discusses using network mapping and multivariate tools to analyze metabolomic data by generating connections between metabolites based on biochemical, chemical, and empirical relationships. These connections can help identify relationships between experimental observations and link the known with unknown. The presentation also provides examples of projects applying these techniques to analyze data from various disease studies involving changes in lipids, proteins, and small molecule metabolites.
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