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In addition, supplementary to the standard paradigm of uniform traffic volumes between randomly interacting node pairs, more realistic gravity traffic patterns are used to simulate the flows in the network.
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In this case, the subgraph corresponds to a pair of interacting nodes, each with self-interactions.
One solution is to decompose such an interaction network into communities of densely interacting nodes and imply functional modules.
The interactions can be either pairwise or cliques of interacting nodes.
Furthermore, the algorithm iterates over all the pairs of interacting nodes, and connects those members for which there is physical interaction in the corresponding PPI database.
Each interaction was associated with the Cartesian product of the labels of the interacting nodes.
Until recently, there has been only limited success in extending the theory to a network of interacting nodes.
In recent years, there is aroused interest in expressing complex systems as networks of interacting nodes.
The topology of the interaction network is then determined by the distribution function of the required amount of shared information between the interacting nodes.
We compiled a catalogue of the protein domains encoded by those fusion proteins and visualized them as a network of interacting nodes, obtaining a global view of the protein domains that are brought together to the same fusion proteins.
The information-theoretic approach we would like to present in this paper is quite generic and promises to be widely applicable to systems which can be described in terms of networks of interacting nodes.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com