Dynamics of content-based networks

Content-based networks are introduced and their topological properties are outlined. A content-based model with Random Boolean dynamics, designed to mimic the gene regulation network, exhibits an increase in the number and complexity of attractors for increasing number of nodes. However, contrary to expectations based on Mean Field calculations for random scale-free networks, the attractors are not chaotic, even for average connectivities in excess of 2. Thus, the present model offers a promising tool for understanding complex biological networks.