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Keywords:

  • Networks;
  • learning;
  • signal transduction;
  • transport.

Abstract

Complex systems are successfully reduced to interacting elements via the network concept. Transport plays a key role in the survival of networks – for example the specialized signaling cascades of cellular networks filter noise and efficiently adapt the network structure to new stimuli. However, our general understanding of transport mechanisms and signaling pathways in complex systems is yet limited. Here we summarize the key network structures involved in transport, list the solutions available to overloaded systems for relaxing their load and outline a possible method for the computational determination of signaling pathways. We highlight that in addition to hubs, bridges and the network skeleton, the overlapping modular structure is also essential in network transport. Path-lenghts in the module-space of the yeast protein-protein interaction network indicated that module-based paths may cross fewer modular boundaries than shortest paths. Moreover, by locating network elements in the space of overlapping network modules and evaluating their distance in this ‘module space’, it may be possible to approximate signaling pathways computationally, which, in turn could serve the identification of signaling pathways of complex systems. Our model may be applicable in a wide range of fields including traffic control or drug design.