  Understanding how the structure of within-system interactions affects the
dynamics of the system is important in many areas of science. We extend a
network dynamics modeling platform DSGRN, which combinatorializes both dynamics
and parameter space to construct finite but accurate summaries of network
dynamics, to new types of interactions. While the standard DSGRN assumes that
each network edge controls the rate of abundance of the target node, the new
edges may control either activity level or a decay rate of its target. While
motivated by processes of post-transcriptional modification and ubiquitination
in systems biology, our extension is applicable to the dynamics of any signed
directed network.
