复杂网络中有色模体的信息含量
Information content of colored motifs in complex networks
摘要：
我们研究复杂的网络，其中网络的节点被标记为不同的颜色，这取决于节点的功能（彩色图），使用信息理论应用于这样的网络中的图案的分布。我们发现，彩色图案可以被视为网络的积木（比无色的结构图案可以），这些图案出现在网络中的相对频率可以用来定义网络的信息内容。该信息以这样的方式定义，即具有随机着色的网络（但保持具有不同颜色的节点的相对数量相同）具有零颜色信息内容。因此，彩色图案信息捕获经由选择维持的图案中的着色的异常性。研究了C. elegans大脑以及网络中彩色基序信息的进化，反映了数字生命生物基因组中指令之间的相互作用。虽然我们发现彩色基序信息似乎捕捉到了C。elegans大脑（其中节点的颜色分配是直接的），不明显的是，在进化过程中，着色的基序信息内容是否总是增加，如从捕获网络复杂性的测量所预期的那样。对于一个单一的选择颜色分配的数字生命形式Avida的指令，我们发现，而彩色基序信息内容增加或减少在进化过程中，这取决于如何组织的基因组，因此可能是一个有趣的工具，解剖基因组重排。
英文摘要：
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 the evolution of colored motif information in networks that reflect the interaction between instructions in genomes of digital life organisms. While we find that colored motif information appears to capture essential functionality in the C. elegans brain (where the color assignment of nodes is straightforward) it is not obvious whether the colored motif information content always increases during evolution, as would be expected from a measure that captures network complexity. For a single choice of color assignment of instructions in the digital life form Avida, we find rather that colored motif information content increases or decreases during evolution, depending on how the genomes are organized, and therefore could be an interesting tool to dissect genomic rearrangements.
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