ABSTRACT
The interactions between the different molecules that in one way or another regulate the functioning of the biological system at hand can be considered as an abstract space. In this way, biological network of specific components can be defined and characterized. The fact that the construction of networks as graphs must reflect the particular identity of the interacting components explains immediately why the knowledge of degree distributions is not enough to characterize them. The important feature of the small-world model is that distant points on the network get access to each other: only a small number of shortcuts will thus allow the network, although being still fairly sparse, to ‘communicate’ efficiently across all nodes. The literature on networks emerging within the statistical physics community has literally exploded since its inception. The existence of motifs can be used to construct an algorithmic procedure for the detection and significance decision of local network elements.
