Computing Bacterial Evolvability Using Individual-Based Models

Computing Bacterial Evolvability Using Individual-Based Models

Richard Gergory (University of Liverpool, UK), Richard Vlachos (University of Liverpool, UK), Ray C. Paton (University of Liverpool, UK), John W. Palmer (University of Liverpool, UK), Q. H. Wu (University of Liverpool, UK) and Jon R. Saunders (University of Liverpool, UK)
Copyright: © 2005 |Pages: 34
DOI: 10.4018/978-1-59140-333-3.ch007
OnDemand PDF Download:
$37.50

Abstract

This chapter describes two approaches to individual-based modelling that are based on bacterial evolution and bacterial ecologies. Some history of the individual-based modelling approach is presented and contrasted to traditional methods. Two related models of bacterial evolution are then discussed in some detail. The first model consists of populations of bacterial cells, each bacterial cell containing a genome and many gene products derived from the genome. The genomes themselves are slowly mutated over time. As a result, this model contains multiple time scales and is very fine-grained. The second model employs a coarser-grained, agent-based architecture designed to explore the evolvability of adaptive behavioural strategies in artificial bacterial ecologies. The organisms in this approach are represented by mutating learning classifier systems. Finally, the subject of computability on parallel machines and clusters is applied to these models, with the aim of making them efficiently scalable to the point of being biologically realistic by containing sufficient numbers of complex individuals.

Complete Chapter List

Search this Book:
Reset
Dedication
Table of Contents
Acknowledgments
Marian Gheorghe
Chapter 1
Gheorghe Paun
Membrane computing is a branch of natural computing whose initial goal was to abstract computing models from the structure and the functioning of... Sample PDF
Membrane Computing: Main Ideas, Basic Results, Applications
$37.50
Chapter 2
Vincenzo Manca, Giuditta Franco, Giuseppe Scollo
Classical dynamics concepts are analysed in the basic mathematical setting of state transition systems where time and space are both completely... Sample PDF
State Transition Dynamics: Basic Concepts and Molecular Computing Perspectives
$37.50
Chapter 3
Lila Kari, Elena Losseva, Petr Sosik
This chapter looks at the question of managing errors that arise in DNA-based computation. Due to the inaccuracy of biochemical reactions, the... Sample PDF
DNA Computing and Errors: A Computer Science Perspective
$37.50
Chapter 4
Carlos Martin-Vide, Victor Mitrana
The goal of this chapter is to survey, in a systematic and uniform way, the main results regarding different computational aspects of hybrid... Sample PDF
Networks of Evolutionary Processors: Results and Perspectives
$37.50
Chapter 5
Andrés Cordón-Franco, Miguel A. Gutiérrez-Naranjo, Mario J. Pérez-Jiménez, Agustín Riscos-Núñez
This chapter is devoted to the study of numerical NP-complete problems in the framework of cellular systems with membranes, also called P systems... Sample PDF
Cellular Solutions to Some Numerical NP-Complete Problems: A Prolog Implementation
$37.50
Chapter 6
Jean-Louis Giavitto, Olivier Michel
Biology has long inspired unconventional models of computation to computer scientists. This chapter focuses on a model inspired by biological... Sample PDF
Modeling Development Processes in MGS
$37.50
Chapter 7
Richard Gergory, Richard Vlachos, Ray C. Paton, John W. Palmer, Q. H. Wu, Jon R. Saunders
This chapter describes two approaches to individual-based modelling that are based on bacterial evolution and bacterial ecologies. Some history of... Sample PDF
Computing Bacterial Evolvability Using Individual-Based Models
$37.50
Chapter 8
Gabriel Ciobanu
In this chapter a model of the molecular networks, created by using a network of communicating automata, is described as a dynamic structure... Sample PDF
On a Formal Model of the T Cell and Its Biological Feedback
$37.50
Chapter 9
Petros Kefalas, G. Eleftherakis, I. Stamatopoulou
Multi-agent systems are highly dynamic since the agents’ abilities and the system configuration often changes over time. In some ways, such... Sample PDF
Formal Modelling of the Dynamic Behaviour of Biology-Inspired, Agent-Based Systems
$37.50
About the Authors