The holland broadcast language and the modeling of biochemical networks

  • Authors:

  • James Decraene;George G. Mitchell;Barry McMullin;Ciaran Kelly

  • Affiliations:

  • Artificial Life Laboratory, Research Institute for Networks and Communication Engineering, School of Electronic Engineering, Dublin City University, Ireland;Artificial Life Laboratory, Research Institute for Networks and Communication Engineering, School of Electronic Engineering, Dublin City University, Ireland;Artificial Life Laboratory, Research Institute for Networks and Communication Engineering, School of Electronic Engineering, Dublin City University, Ireland;Artificial Life Laboratory, Research Institute for Networks and Communication Engineering, School of Electronic Engineering, Dublin City University, Ireland

  • Venue:
  • EuroGP'07 Proceedings of the 10th European conference on Genetic programming
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

The Broadcast Language is a programming formalism devised by Holland in 1975, which aims at improving the efficiency of Genetic Algorithms (GAs) during long-term evolution. The key mechanism of the Broadcast Language is to allow GAs to employ an adaptable problem representation. Fixed problem encoding is commonly used by GAs but may limit their performance in particular cases. This paper describes an implementation of the Broadcast Language and its application to modeling biochemical networks. Holland presented the Broadcast Language in his book "Adaptation in Natural and Artificial Systems" where only a description of the language was provided, without any implementation. Our primary motivation for this work was the fact that there is currently no published implementation of the Broadcast Language available. Secondly, no additional examination of the Broadcast Language and its applications can be found in the literature. Holland proposed that the Broadcast Language would be suitable for the modeling of biochemical models. However, he did not support this belief with any experimental work. In this paper, we propose an implementation of the Broadcast Language which is then applied to the modeling of a signal transduction network. We conclude the paper by proposing that with some refinements it will be possible to use the Broadcast Language to evolve biochemical networks in silico.