Strong regulatory graphs

Fuente: arXiv
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Hauptverfasser: Gustafsson, Patric, Petre, Ion
Format: Preprint
Veröffentlicht: 2023
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author Gustafsson, Patric
Petre, Ion
author_facet Gustafsson, Patric
Petre, Ion
contents Logical modeling is a powerful tool in biology, offering a system-level understanding of the complex interactions that govern biological processes. A gap that hinders the scalability of logical models is the need to specify the update function of every vertex in the network depending on the status of its predecessors. To address this, we introduce in this paper the concept of strong regulation, where a vertex is only updated to active/inactive if all its predecessors agree in their influences; otherwise, it is set to ambiguous. We explore the interplay between active, inactive, and ambiguous influences in a network. We discuss the existence of phenotype attractors in such networks, where the status of some of the variables is fixed to active/inactive, while the others can have an arbitrary status, including ambiguous.
format Preprint
id arxiv_https___arxiv_org_abs_2306_08261
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Strong regulatory graphs
Gustafsson, Patric
Petre, Ion
Discrete Mathematics
Molecular Networks
Quantitative Methods
Logical modeling is a powerful tool in biology, offering a system-level understanding of the complex interactions that govern biological processes. A gap that hinders the scalability of logical models is the need to specify the update function of every vertex in the network depending on the status of its predecessors. To address this, we introduce in this paper the concept of strong regulation, where a vertex is only updated to active/inactive if all its predecessors agree in their influences; otherwise, it is set to ambiguous. We explore the interplay between active, inactive, and ambiguous influences in a network. We discuss the existence of phenotype attractors in such networks, where the status of some of the variables is fixed to active/inactive, while the others can have an arbitrary status, including ambiguous.
title Strong regulatory graphs
topic Discrete Mathematics
Molecular Networks
Quantitative Methods
url https://arxiv.org/abs/2306.08261