Coevolving Boolean and Multi-Valued Regulatory Networks

2023/02/03 by Larry Bull, Bull, Larry
Biochemistry, Genetics and Molecular Biology · #Evolution and Genetic Dynamics #FOS: Biological sciences #FOS: Computer and information sciences #Gene Regulatory Network Analysis #Molecular Networks (q-bio.MN) #Neural and Evolutionary Computing (cs.NE)

paper · pdf · doi:10.48550/arxiv.2302.01694

openalex publication_date 2023/02/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Random Boolean networks have been used widely to explore aspects of gene regulatory networks. A modified form of the model through which to systematically explore the effects of increasing the number of gene states has previously been introduced. In this paper, these discrete dynamical networks are coevolved within coupled, rugged fitness landscapes to explore their behaviour. Results suggest the general properties of the Boolean model remain with higher valued logic regardless of the update scheme or fitness sampling method. Introducing topological asymmetry in the coevolving networks is seen to alter behaviour.

Related

• Evolving Diploid Boolean and Multi-Valued Gene Networks
• Biologically meaningful regulatory logic enhances the convergence rate in Boolean networks and bushiness of their state transition graph
• Ensembles, Dynamics, and Cell Types: Revisiting the Statistical\n Mechanics Perspective on Cellular Regulation
• Dynamical regimes in non-ergodic random Boolean networks
• Guiding the Self-organization of Random Boolean Networks