Cummins, BreeGameiro, MarcioGedeon, TomasKepley, ShaneMischaikow, KonstantinZhang, Lun2023-03-222023-03-222022-09Cummins, B., Gameiro, M., Gedeon, T., Kepley, S., Mischaikow, K., & Zhang, L. (2022). Extending combinatorial regulatory network modeling to include activity control and decay modulation. SIAM Journal on Applied Dynamical Systems, 21(3), 2096-2125.1536-0040https://scholarworks.montana.edu/handle/1/17769© SIAMUnderstanding 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.en-UScopyright Society for Industrial & Applied Mathematics 2022https://perma.cc/LD5P-HDAPnetwork dynamicsgene regulationmathematical biologyArticle