MeMo (Metabolomic Modelling) schema has been designed primarily to capture data related to yeast metabolomics with an emphasis on metabolomic footprinting as a strategy for functional genomics. Nonetheless, the general schema is applicable to a wide range of metabolomics experiments. The core schema (modelled in UML) consists of abstract classes, which can be specialised in order to embrace different types of experiments, results, organisms, etc. It is designed to capture information about the overall experimental cycle, including growth, sample preparation and analytical experiments. Information about specific conditions, protocols and parameters used in wet experiments (i.e. the metadata) is needed to interpret the experimental results and support their comparison and reproducibility. In addition, metabolomics experiments in the post-genomic era often need to be extended beyond the traditional wet experimental framework. In order to process the vast amount of metabolomics data, data mining experiments (or dry experiments) need to be performed in silico to extract knowledge. Our model has been implemented as a relational database and an XML schema. In both cases, flexibility has been supported by using a modular approach where different metadata modules (implemented as separate XML schemas) can be plugged into the overall metabolomics schema (in both relational and XML versions).
The MeMo specification (version 1.1) is given as a design document.