Information content of colored motifs in complex networks
Christoph Adami, Jifeng Qian, Matthew Rupp, and Arend Hintze

TL;DR
This paper introduces a method using information theory to analyze the significance of colored motifs in complex networks, revealing their role as fundamental building blocks and their potential to reflect functional and evolutionary aspects.
Contribution
It presents a novel approach to quantify the information content of colored motifs, linking motif frequency to network functionality and evolution, with applications to biological and digital life networks.
Findings
Colored motifs serve as key network building blocks.
Colored motif information correlates with network functionality.
Evolution of colored motif information varies with network organization.
Abstract
We study complex networks in which the nodes of the network are tagged with different colors depending on the functionality of the nodes (colored graphs), using information theory applied to the distribution of motifs in such networks. We find that colored motifs can be viewed as the building blocks of the networks (much more so than the uncolored structural motifs can be) and that the relative frequency with which these motifs appear in the network can be used to define the information content of the network. This information is defined in such a way that a network with random coloration (but keeping the relative number of nodes with different colors the same) has zero color information content. Thus, colored motif information captures the exceptionality of coloring in the motifs that is maintained via selection. We study the motif information content of the C. elegans brain as well as…
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