Design of artificial genetic regulatory networks with multiple delayed adaptive responses

TL;DR

This paper presents a method for designing complex genetic regulatory networks with multiple delayed adaptive responses using an evolutionary algorithm, enabling customizable and intricate network behaviors.

Contribution

It introduces a novel evolutionary approach to construct genetic networks with multiple receptors and outputs capable of delayed adaptive responses, expanding beyond simple models.

Findings

Networks can produce diverse delayed responses.

Output nodes exhibit responses based on different receptors.

Complex network structures with shared processing nodes are feasible.

Abstract

Genetic regulatory networks with adaptive responses are widely studied in biology. Usually, models consisting only of a few nodes have been considered. They present one input receptor for activation and one output node where the adaptive response is computed. In this work, we design genetic regulatory networks with many receptors and many output nodes able to produce delayed adaptive responses. This design is performed by using an evolutionary algorithm of mutations and selections that minimizes an error function defined by the adaptive response in signal shapes. We present several examples of network constructions with a predefined required set of adaptive delayed responses. We show that an output node can have different kinds of responses as a function of the activated receptor. Additionally, complex network structures are presented since processing nodes can be involved in several input-output pathways.