The University of Southampton
University of Southampton Institutional Repository

Associative memory in gene regulation networks

Watson, Richard, Buckley, C. L., Mills, Rob and Davies, Adam, (2010) Associative memory in gene regulation networks Fellerman, Harold, Dörr, Mark, Hanczyc, Martin M., Ladegaard Laursen, Lone, Maurer, Sarah, Merkle, Daniel, Monnard, Pierre-Alain, Stoy, Kasper and Rasmussen, Steen (eds.) In Artificial Life XII: Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems. MIT Press., pp. 659-666.

Record type: Conference or Workshop Item (Paper)

Abstract

The pattern of gene expression in the phenotype of an organism is determined in part by the dynamical attractors of the organism’s gene regulation network. Changes to the connections in this network over evolutionary time alter the adult gene expression pattern and hence the fitness of the organism. However, the evolution of structure in gene expression networks (potentially reflecting past selective environments) and its affordances and limitations with respect to enhancing evolvability is poorly understood in general. In this paper we model the evolution of a gene regulation network in a controlled scenario. We show that selected changes to connections in the regulation network make the currently selected gene expression pattern more robust to environmental variation. Moreover, such changes to connections are necessarily ‘Hebbian’ – ‘genes that fire together wire together’ – i.e. genes whose expression is selected for in the same selective environments become co-regulated. Accordingly, in a manner formally equivalent to well-understood learning behaviour in artificial neural networks, a gene expression network will therefore develop a generalised associative memory of past selected phenotypes. This theoretical framework helps us to better understand the relationship between homeostasis and evolvability (i.e. selection to reduce variability facilitates structured variability), and shows that, in principle, a gene regulation network has the potential to develop ‘recall’ capabilities normally reserved for cognitive systems.

PDF chap40.pdf - Version of Record
Download (1MB)

More information

Published date: 2010
Organisations: Agents, Interactions & Complexity, EEE

Identifiers

Local EPrints ID: 339763
URI: http://eprints.soton.ac.uk/id/eprint/339763
ISBN: 978-0-262-29075-3
PURE UUID: de6cad9f-f15b-4135-b0e8-7e42138bd12f

Catalogue record

Date deposited: 30 May 2012 08:46
Last modified: 18 Jul 2017 05:52

Export record

Contributors

Author: Richard Watson
Author: C. L. Buckley
Author: Rob Mills
Author: Adam Davies
Editor: Harold Fellerman
Editor: Mark Dörr
Editor: Martin M. Hanczyc
Editor: Lone Ladegaard Laursen
Editor: Sarah Maurer
Editor: Daniel Merkle
Editor: Pierre-Alain Monnard
Editor: Kasper Stoy
Editor: Steen Rasmussen

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×