Many new structural patterns have been discovered in diverse biological, social and information networks. One of them are metabolic networks, the most widely studied large scale networks in biology, known to have a power law degree distribution and the exponent _ is observed to be the same for all species. However, empirical evidence elucidating the nature of the process that gives rise to such structure is lacking this far. In this paper we review facts about power law distribution as relevant to metabolic networks. In particular we concentrate on the evolutionary and other implications of such a power law distribution.
The study of metabolic pathways has been the key areas of interest for researchers in bioinformatics. The data in the form of pathways provides an organizational and simple form of representing data. Such representation is easy to understand and implement. One of the most basic elements of these pathways is switches. Switches may used to connect two complex pathways or may be used in one big pathway itself to regulate some part of a complex pathway. Many cellular components are found to be performing as switches regulating various activities of the cell. It is of foremost importance to identify such switches in a network to study its effect on the regulation and the function of the cell.