Computational biologists, specifically those who utilize network models, are hoping to make this idea more concrete. It's well-known now that some real-world (i

Computational biologists, specifically those who utilize network models, are hoping to make this idea more concrete. It's well-known now that some real-world (including biological) networks are scale-free (mathematically, their degree distribution follows a power law). As an example, many gene networks have "hub" genes, that are related to several genes, whereas the median connectivity of a gene is fairly low. Separately but also related, there's a growing sentiment that biological networks are self-similar - higher-level network-modeled abstractions are in fact topologically similar to lower-level subnetworks. This analogy may seem almost Hofstadter-esque at this point, but in a few years, who knows... Some links: [1] https://www.nature.com/articles/srep07628 https://www.nature.com/articles/srep07628 [2] http://rsif.royalsocietypublishing.org/content/9/74/2131 http://rsif.royalsocietypublishing.org/content/9/74/2131