  Metabolic networks consist of linked functional components, or modules. The
mechanism underlying metabolic network modularity is of great interest not only
to researchers of basic science but also to those in fields of engineering.
Previous studies have suggested a theoretical model, which proposes that a
change in the evolutionary goal (system-specific purpose) increases network
modularity, and this hypothesis was supported by statistical data analysis.
Nevertheless, further investigation has uncovered additional possibilities that
might explain the origin of network modularity. In this work, we propose an
evolving network model without tuning parameters to describe metabolic
networks. We demonstrate, quantitatively, that metabolic network modularity can
arise from simple growth processes, independent of the change in the
evolutionary goal. Our model is applicable to a wide range of organisms, and
appears to suggest that metabolic network modularity can be more simply
determined than previously thought. Nonetheless, our proposition does not serve
to contradict the previous model; it strives to provide an insight from a
different angle in the ongoing efforts to understand metabolic evolution, with
the hope of eventually achieving the synthetic engineering of metabolic
networks.

Molecular Networks;Data Analysis, Statistics and Probability