Transport is an important function in many network systems and understanding its behavior on biological, social, and technological networks is crucial for a wide range of applications. However, it is a property that is not well understood in these systems, probably because of the lack of a general theoretical framework. Here, based on the finding that renormalization can be applied to bionetworks, we develop a scaling theory of transport in self-similar networks. We demonstrate the networks invariance under length scale renormalization, and we show that the problem of transport can be characterized in terms of a set of critical exponents. The scaling theory allows us to determine the influence of the modular structure on transport in metabolic and protein-interaction networks. We also generalize our theory by presenting and verifying scaling arguments for the dependence of transport on microscopic features, such as the degree of the nodes and the distance between them. Using transport concepts such as diffusion and resistance, we exploit this invariance, and we are able to explain, based on the topology of the network, recent experimental results on the broad flow distribution in metabolic networks.
Scaling theory of transport in complex biological networks
L. Gallos,Chaoming Song,S. Havlin,H. Makse
Published 2007 in Proceedings of the National Academy of Sciences of the United States of America
ABSTRACT
PUBLICATION RECORD
- Publication year
2007
- Venue
Proceedings of the National Academy of Sciences of the United States of America
- Publication date
2007-02-06
- Fields of study
Biology, Medicine, Physics, Mathematics
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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