The last century brought with it unprecedented technological and scientific progress, rooted in the success of the reductionist approach. For many current scientific problems, however, it is not possible to predict the behavior of a system from an understanding of its (often identical) elementary constituents and their individual interactions. For these systems, we need to develop new methods to gain insight into their properties and dynamics. During the last few years, network approaches have shown great promise in this direction, offering new tools to analyze and understand a host of complex systems (1–4). A much studied example of the network approach concerns communication systems like the Internet and the World Wide Web, which are modeled as networks with nodes being routers (5) or web pages (6) and the links being the physical wires or URLs. The network approach also lends itself to the analysis of societies, with people as nodes and the connections between the nodes representing friendships (7), collaborations (8,9), sexual contacts (10), or coauthorship of scientific papers (11), to name a few possibilities. It seems that the more we scrutinize the world surrounding us, the more we realize that we are inextricably entangled in myriad interacting webs; to describe them we need to understand the architecture of these various networks that nature and technology offers to us.

Biological systems ranging from food webs in ecology to biochemical interactions in molecular biology can benefit greatly from being analyzed as networks. In particular, in the cell, the variety of interactions between genes, proteins, and metabolites are well captured by network representations, especially with the availability of veritable mountains of interaction data from genomics approaches.