Graphs are one the useful network modeling tools to analyse the structure and dynamic of different networks regardless of their nature or origin.
common properties of networks help you to analyse or design networks (this inspiration may arises from a social or economic network to apply in biological systems). metabolic or protein interaction networks are studied by this method and the results were conceivable.
Now the question is how graph based modeling can be practiced to study the interactions and correlations between different systems,for example interaction of metabolic networks with nervous system (of course at first,it's necessary to define such graphical models for nervous system)?
Which probabilistic mediators would be needed and what will be properties of such bridges between different cooperating systems for biological networks?
This might be of help. Modelling coupled evolution of gene regulatory and metabolic networks (http://www.stats.ox.ac.uk/__data/assets/pdf_file/0018/6156/Hong_Noh_2010.pdf)
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- Biological Science
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