Beyond Boolean networks: new tools for the steady state analysis of multivalued networks

Fuente: arXiv
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Hauptverfasser: Galofre, J. García, Millán, M. Pérez, Rial, A. Galarza, Laubenbacher, R., Dickenstein, A.
Format: Preprint
Veröffentlicht: 2024
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author Galofre, J. García
Millán, M. Pérez
Rial, A. Galarza
Laubenbacher, R.
Dickenstein, A.
author_facet Galofre, J. García
Millán, M. Pérez
Rial, A. Galarza
Laubenbacher, R.
Dickenstein, A.
contents Boolean networks can be viewed as functions on the set of binary strings of a given length, described via logical rules. They were introduced as dynamic models into biology, in particular as logical models of intracellular regulatory networks involving genes, proteins, and metabolites. Since genes can have several modes of action depending on their expression levels, binary variables are often not sufficiently rich, requiring the use of multivalued networks instead. In this paper, we explore the multivalued generalization of Boolean networks by writing the standard $(\wedge, \vee, \lnot)$ operations on $\{0, 1\}$ in terms of the operations $(\odot, \oplus, \neg)$ on $\big\{0,\frac{1}{m}, \frac{2}{m}, \dots, \frac{m-1}{m}, 1\big\}$ from multivalued logic. We recall the basic theory of this mathematical framework, and give a novel algorithm for computing the fixed points that in many cases has essentially the same complexity as in the binary case. Our approach provides a biologically intuitive representation of the network. Furthermore, it uses tools to compute lattice points in rational polytopes, tapping a rich area of algebraic combinatorics as a source for combinatorial algorithms for network analysis. An implementation of the algorithm is provided.
format Preprint
id arxiv_https___arxiv_org_abs_2404_16760
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Beyond Boolean networks: new tools for the steady state analysis of multivalued networks
Galofre, J. García
Millán, M. Pérez
Rial, A. Galarza
Laubenbacher, R.
Dickenstein, A.
Dynamical Systems
Quantitative Methods
Boolean networks can be viewed as functions on the set of binary strings of a given length, described via logical rules. They were introduced as dynamic models into biology, in particular as logical models of intracellular regulatory networks involving genes, proteins, and metabolites. Since genes can have several modes of action depending on their expression levels, binary variables are often not sufficiently rich, requiring the use of multivalued networks instead. In this paper, we explore the multivalued generalization of Boolean networks by writing the standard $(\wedge, \vee, \lnot)$ operations on $\{0, 1\}$ in terms of the operations $(\odot, \oplus, \neg)$ on $\big\{0,\frac{1}{m}, \frac{2}{m}, \dots, \frac{m-1}{m}, 1\big\}$ from multivalued logic. We recall the basic theory of this mathematical framework, and give a novel algorithm for computing the fixed points that in many cases has essentially the same complexity as in the binary case. Our approach provides a biologically intuitive representation of the network. Furthermore, it uses tools to compute lattice points in rational polytopes, tapping a rich area of algebraic combinatorics as a source for combinatorial algorithms for network analysis. An implementation of the algorithm is provided.
title Beyond Boolean networks: new tools for the steady state analysis of multivalued networks
topic Dynamical Systems
Quantitative Methods
url https://arxiv.org/abs/2404.16760