Keck Graduate Institute of Applied Life Sciences, Claremont, CA 91711, USA.
Artif Life. 2011 Fall;17(4):375-90. doi: 10.1162/artl_a_00045. Epub 2011 Jul 15.
We study complex networks in which the nodes are tagged with different colors depending on their function (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 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 its information content. 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.
我们研究了节点根据其功能被标记为不同颜色的复杂网络（彩色图），使用信息论来研究这些网络中模式的分布。我们发现，彩色模式可以被视为网络的构建块（比非彩色结构模式更重要），并且这些模式在网络中出现的相对频率可以用来定义网络的信息含量。这种信息的定义方式是，具有随机着色的网络（但保持不同颜色的节点数量相对相同）的颜色信息含量为零。因此，彩色模式信息捕捉了通过选择维持的模式着色的异常性。我们研究了秀丽隐杆线虫大脑的模式信息含量，以及反映数字生命生物体基因组指令之间相互作用的网络中彩色模式信息的演化。虽然我们发现彩色模式信息似乎可以捕捉秀丽隐杆线虫大脑中的基本功能（节点的颜色分配很直接），但在进化过程中，彩色模式信息含量是否总是增加，这并不明显，因为这是一种捕捉网络复杂性的度量标准。对于数字生命形式 Avida 中指令的单一颜色分配选择，我们发现，彩色模式信息含量在进化过程中会增加或减少，具体取决于基因组的组织方式，因此它可能是剖析基因组重排的一个有趣工具。
