Abstract

The computational reconstruction and analysis of cellular models of microbial metabolism is one of the great success stories of systems biology. The extent and quality of metabolic network reconstructions is, however, limited by the current state of biochemical knowledge. Can experimental high-throughput data be used to improve and expand network reconstructions to include unexplored areas of metabolism? Recent advances in experimental technology and analytical methods bring this aim an important step closer to realization. Data integration will play a particularly important part in exploiting the new experimental opportunities.

Author affiliations

1. Rainer Breitling is at the Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9751 NN Haren, The Netherlands.
2. Dennis Vitkup is at the Center for Computational Biology and Bioinformatics, Department of Biomedical Informatics, Columbia University, New York, New York 10032, United States.
3. Michael P. Barrett is at the Division of Infection and Immunity, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom.

Correspondence to: Rainer Breitling¹ Email: r.breitling@rug.nl

Correspondence to: Dennis Vitkup² Email: vitkup@dbmi.columbia.edu

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