Abstract
AbstractComplex systems of intracellular biochemical reactions have a central role in regulating cell identities and functions. Biochemical reaction systems are typically studied using the language and tools of graph theory. However, graph representations only describe pairwise interactions between molecular species and so are not well suited to modelling complex sets of reactions that may involve numerous reactants and/or products. Here, we make use of a recently developed hypergraph theory of chemical reactions that naturally allows for higher-order interactions to explore the geometry and quantify functional redundancy in biochemical reactions systems. Our results constitute a general theory of automorphisms for oriented hypergraphs and describe the effect of automorphism group structure on hypergraph Laplacian spectra.
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Ecology, Evolution, Behavior and Systematics,Statistics and Probability
Reference47 articles.
1. Andreotti E, Mulas R Signless Normalized Laplacian for Hypergraphs. ArXiv:2005.14484
2. Bader G, Betel D, Hogue C (2003) BIND: the biomolecular interaction network database. Nucleic Acids Res, 31(1):248. https://doi.org/10.1093/nar/gkg056
3. Bader G, Donaldson I, Wolting C, Ouellette B, Pawson T, Hogue C (2001) BIND: the biomolecular interaction network database. Nucleic Acids Res, 29(1):242. https://doi.org/10.1093/nar/29.1.242
4. Banerjee A, Jost J (2009) Graph spectra as a systematic tool in computational biology. Discrete Appl Math, 157(10):2425
5. Barabási AL et al (2016) Network science. Cambridge University Press, Cambridge
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