Several technologies are widely used in metabolomics investigations including mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR).  The basic use of these technologies and challenges for identification and quantification of metabolites in biological systems will be reviewed along with emerging new technologies that will contribute to the metabolomics knowledge base.

Diverse transformation algorithms are used to derive the identification and quantification of metabolites, fluxes, and metabolomic profiles from raw instrument data.  Specific technical aspects of data acquisition, processing and analysis used in metabolomics require informatics support and can be platform dependent.  Metadata needed to describe these processes and their effects on interpretation and integration of data for publication will be presented.

This discussion will address the basic metadata needed to describe instrumentation and processing of raw data to forms that can be used to describe metabolites and metabolic profiles.

Several model systems are being used to investigate mechanistic understanding of metabolomes and their temporal-spatial dynamics with regard to biological pathways.  Understanding the metadata needed to describe these experiments and intricacies of each model system will provide a foundation for comparing high throughput experimental results.

Metabolomics has great potential for describing both normal and disease processes in tissues and systems biology.  Clinical and preclinical investigation into biomarker discovery, diagnostics, predictive toxicology and understanding of human nutritional and energy balances through interrogation of body fluids and tissues are being conducted with metabolomics approaches.  Understanding what metadata information must be captured and conveyed for these uses will be vital to the development of clinical metabolomics approaches to translational medicine.