ABSTRACT
In previous chapters of this book, our emphasis has been mainly on modeling biomolecular networks by experimental, theoretical and computational means, and on the validation and filtering of these models. We have, to a rather limited extent, discussed the use of network information for the inference of biological function and to help clarify disease states. Furthermore, we have barely touched upon how knowledge of interactions and of their evolution can help illuminate deeper issues such as the modularity of biological organization and organismal robustness. These questions are addressed in greater depth in this chapter and the one following it. We are now in a position to ask how network data can be systematically used to advance biology and medicine. A key concept central to the usefulness of the network approach
to biology or medicine is that of modularity. The modular organization of biological networks has received much attention in recent years, primarily because the modularity of connection patterns is intimately connected to the modularity of biological function. The complexity of biological function can best be understood in terms of components that retain some of the biological properties of interest. Hence it is desirable to reduce complexity down to structural or functional units: the modules. Understanding modularity at the network level allows one to form a basis for understanding the evolution of modularity at the functional level, the links between different functions, and the correlation of their phenotypes. Furthermore, the existence of network modules that are densely interconnected among themselves while being sparsely connected to the rest of the network hints at a type of robustness: targeting a component of a module is likely to degrade the function(s) associated with the specific module while not seriously affecting other modules or the whole organism. We therefore study the topics of modularity and robustness, as they manifest themselves at the network level, together in this chapter. We begin with a classic example in biology: segmental patterning in the embryonic stage of development of the fruit fly
Drosophila melanogaster. Following this, we discuss definitions of modularity in larger networks and their functional significance. Finally, we address dynamical and topological robustness in networks.
