There are a host of potential applications for DNA, including the following:
Social media analysis, where friends and contacts are frequently changing
Communication networks, such as corporate e-mail systems, where evolving patterns emerge over the course of days and weeks
Political networks that change over time as entities gain or lose power
Terrorist cells with frequent changes in structure driven by increasing membership and evolving network connections
Disease modeling, where contagion rates can force rapid changes in the status of nodes within a network
In short, any network with relatively frequent changes over time will be a good candidate for DNA. Networks with infrequent or very slow changes (perhaps tenured faculty at a university or power grid infrastructure networks, to name just two examples) are often adequately addressed by static networks, as temporal analysis adds complexity while shedding little additional insight into network behavior.
There are two distinct...