Title: Investigations on Relationship of Scale-Free Networks to Biological Network Robustness using a Boolean Network Computational Model
Abstract: Dynamical behaviors of biological networks are related to their structural characteristics and thus investigations on such relationships are important in understanding a design principle of biological networks. In this paper, we note that biological networks have a scale-free property where degree distribution of nodes follows a power law and try to elucidate the effects of the scale-free property on the network robustness. Although there have been previous studies on the relationship between the scale-free property and robustness, our understanding is still unclear since they simply focused on the difference of state trajectories, did not consider the network connectivity, and did not examine dynamics over all possible network states. In this regard, we propose a Boolean network model which generates only connected networks and investigate the robustness in terms of the converging attractors over all possible states. Through extensive simulations, we show that scale-free networks are more robust against perturbations than random networks. In addition. it is shown that the scale-free networks generate hub nodes with a considerably large degree but their robustness is very small. This is supported by the observation that the proportion of lethal genes in the set of hub genes is relatively large in a signal transduction network. All these results imply that the scale-free property is an important design principle of biological networks to induce different dynamics from that of random networks.
Publication Year: 2011
Publication Date: 2011-01-01
Language: en
Type: article
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