Basically two approaches to interpret a reconstructed metabolic network exist so far, which differ in the consideration of ubiquitous compounds like H2O, ATP, and NADH, often referred to as current (or currency) metabolites.
As we know, many large-scale systems consisting of interactive individuals, such as food webs, communication networks, social networks, power grids, cellular networks, world wide web, metabolic systems, disease transmission networks and so on [1 3], which are modeled by complex dynamical networks, exist in the real world.
On the one hand, complex networks exist in our daily life with examples including the Internet, the World Wide Web, food webs, electric power grids, cellular and metabolic networks, etc. [2].
Social networks existed long before it.
Multiple "genome-scale" metabolic network reconstructions now exist for C. acetobutylicum[ 9- 12].
We describe how metabolic networks can be represented using stoichiometric matrices and well-defined constraints on metabolic fluxes.
While in [ 29], the control modes of the three involved metabolic networks cannot be identified, which is caused by the incompleteness of the metabolic networks, whose average degrees are in the 'pre-bifurcation' region (where no distinct control modes exist).
In the EM approach, each enzymatic reaction is broken down into a series of elementary reactions, thus preserving the fundamental behavior we know to exist in metabolic networks.
It has been reported that hierarchical modularity exists in metabolic networks of E. coli and S. cerevisiae [ 106, 109].
Several different types of gaps can exist in reconstructed metabolic networks [ 8, 9].
