Rebekah Aduddell ; James Fairbanks ; Amit Kumar ; Pablo S. Ocal ; Evan Patterson et al. - A compositional account of motifs, mechanisms, and dynamics in biochemical regulatory networks

compositionality:13637 - Compositionality, May 13, 2024, Volume 6 (2024) - https://doi.org/10.32408/compositionality-6-2
A compositional account of motifs, mechanisms, and dynamics in biochemical regulatory networksArticle

Authors: Rebekah Aduddell 1; James Fairbanks 2; Amit Kumar 3; Pablo S. Ocal 4; Evan Patterson 5; Brandon T. Shapiro 6

Regulatory networks depict promoting or inhibiting interactions between molecules in a biochemical system. We introduce a category-theoretic formalism for regulatory networks, using signed graphs to model the networks and signed functors to describe occurrences of one network in another, especially occurrences of network motifs. With this foundation, we establish functorial mappings between regulatory networks and other mathematical models in biochemistry. We construct a functor from reaction networks, modeled as Petri nets with signed links, to regulatory networks, enabling us to precisely define when a reaction network could be a physical mechanism underlying a regulatory network. Turning to quantitative models, we associate a regulatory network with a Lotka-Volterra system of differential equations, defining a functor from the category of signed graphs to a category of parameterized dynamical systems. We extend this result from closed to open systems, demonstrating that Lotka-Volterra dynamics respects not only inclusions and collapsings of regulatory networks, but also the process of building up complex regulatory networks by gluing together simpler pieces. Formally, we use the theory of structured cospans to produce a lax double functor from the double category of open signed graphs to that of open parameterized dynamical systems. Throughout the paper, we ground the categorical formalism in examples inspired by systems biology.


Volume: Volume 6 (2024)
Published on: May 13, 2024
Imported on: May 21, 2024
Keywords: Quantitative Biology - Molecular Networks,Mathematics - Category Theory

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