Comparison of two combinatorial models of global network dynamics
Peter Crawford-Kahrl, Bree Cummins, Tomas Gedeon

TL;DR
This paper compares two combinatorial models of biological network dynamics, demonstrating how continuous time ODE systems relate to discrete switching systems through a parameterized Morse graph correspondence.
Contribution
It introduces a method to associate a continuous time L-system with a discrete switching system and compares their global dynamics via Morse graphs.
Findings
Order-preserving map from switching to L-system Morse graphs
Surjective correspondence on attractors
Bijective on fixed point attractors
Abstract
Modeling the dynamics of biological networks introduces many challenges, among them the lack of first principle models, the size of the networks, and difficulties with parameterization. Discrete time Boolean networks and related continuous time switching systems provide a computationally accessible way to translate the structure of the network to predictions about the dynamics. Recent work has shown that the parameterized dynamics of switching systems can be captured by a combinatorial object, called a DSGRN database, that consists of a parameter graph characterizing a finite parameter space decomposition, whose nodes are assigned a Morse graph that captures global dynamics for all corresponding parameters. We show that for a given network there is a way to associate the same type of object by considering a continuous time ODE system with a continuous right-hand side, which we call an…
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Taxonomy
TopicsGene Regulatory Network Analysis · Bioinformatics and Genomic Networks · Microbial Metabolic Engineering and Bioproduction
