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Genome-scale metabolic reconstructions and their analysis with constraint-based modeling techniques have gained enormous momentum. It is a natural next step after sequencing of a genome, as a technique that links top-down systems biology analyses at genome scale with bottom-up systems biology modeling scrutiny.

Metabolic network reconstruction and simulation allows for an in-depth insight into the molecular mechanisms of a particular organism. In particular, these models correlate the genome with molecular physiology. A reconstruction breaks down metabolic pathways (such as glycolysis and the citric acid cycle) into their respective reactions and enzymes, and analyzes them within the perspective of the entire network. In simplified terms, a reconstruction collects all of the relevant metabolic information of an organism and compiles it in a mathematical model. Validation and analysis of reconstructions can allow identification of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. This knowledge can then be applied to create novel biotechnology.