Azimuth originally shared this post:
A paper on networks, systems biology and medicine:
“Proceeding from a topological description of these networks to an appreciation of their role in defining human disease requires recognition of a few important organizing principles derived from network theory. In brief, any network can be viewed as a collection of linked nodes, the distribution of which can range from random to highly clustered. Biological networks are not random collections of
nodes and links, but evolve as clustered collections of genes, regulatory RNAs, proteins, or metabolites. Biological and pathobiological networks are scale-free;
contain few highly connected nodes (hubs) and bottlenecks (nodes that link different highly connected clusters to each other, gaining, as a result, high ‘betweenness centrality’; manifest the small-world effect and disassortativity (highly connected
nodes, or hubs, typically avoid linking to one another); and contain motifs with predictable functional consequences (feedback loops, oscillators, etc.). All of the biological networks relevant to disease manifest these properties, as well, which gives us a starting point from which to begin to identify those subnetworks or modules that are responsible for a specific pathobiological process or a specific disease.”
Of course we should expect some of the general principles here may apply in ecology and elsewhere, too!