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Technological advances in analytical instrumentation and advances in data modeling are working in synergy to open up new perspectives and research agendas in metabolic research. Thanks to the legacy of the Human Genome Project and its continued impact in the post-genomic era, metabolism is now thought of in a whole-genome context, even when the focus is on a single metabolite and individual metabolic reactions. For a few model organisms we now have extensive, and in some cases complete, information about components that perform integrated metabolic functions. This promises a true paradigm shift in our understanding of the processes of metabolism, but also poses new challenges. As complex and coordinated global behaviors are observed in what were thought to be "simple" organisms, many challenges remain in the experimental domain, as well as in the integration of data generated by increasingly high-throughput analytical techniques. Indeed, in the new era of metabolic research, mathematical and computational modeling is expected to play an increasingly important role. For many complex biochemical phenomena, use of mathematical models may be the best way to build a consistent picture and generate testable hypotheses based on complex yet inevitably incomplete data sets.[...

Metabolites: A Novel Platform for Converging Research on Metabolism and Metabolomics