Boolean Threshold Networks as Models of Genotype-Phenotype Maps

Chico Q. Camargo, Ard A. Louis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Boolean threshold networks (BTNs) are a class of mathematical models used to describe complex dynamics on networks. They have been used to study gene regulation, but also to model the brain, and are similar to artificial neural networks used in machine learning applications. In this paper we study BTNs from the perspective of genotype-phenotype maps, by treating the network’s set of nodes and connections as its genotype, and dynamic behaviour of the model as its phenotype. We show that these systems exhibit (1) Redundancy, that is many genotypes map to the same phenotypes; (2) Bias, the number of genotypes per phenotypes varies over many orders of magnitude; (3) Simplicity bias, simpler phenotypes are exponentially more likely to occur than complex ones; (4) Large robustness, many phenotypes are surprisingly robust to random perturbations in the parameters, and (5) this robustness correlates positively with the evolvability, the ability of the system to find other phenotypes by point mutations of the parameters. These properties should be relevant for the wide range of systems that can be modelled by BTNs.

Original languageEnglish
Title of host publicationComplex Networks XI - Proceedings of the 11th Conference on Complex Networks, CompleNet 2020
EditorsHugo Barbosa, Ronaldo Menezes, Jesus Gomez-Gardenes, Bruno Gonçalves, Giuseppe Mangioni, Marcos Oliveira
PublisherSpringer
Pages143-155
Number of pages13
ISBN (Print)9783030409425
DOIs
StatePublished - 2020
Event11th International Conference on Complex Networks, CompleNet 2020 - Exeter, United Kingdom
Duration: 31 Mar 20203 Apr 2020

Publication series

NameSpringer Proceedings in Complexity
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692

Conference

Conference11th International Conference on Complex Networks, CompleNet 2020
Country/TerritoryUnited Kingdom
CityExeter
Period31/03/203/04/20

Bibliographical note

Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

Keywords

  • Boolean networks
  • Gene regulatory networks
  • Genotype-phenotype maps
  • Input-output maps

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