Modeling Development Processes in MGS

Modeling Development Processes in MGS

Jean-Louis Giavitto (CNRS – University of Évry Val d’Essonne – Genopole, France) and Olivier Michel (University of Évry Val d’Essonne – Genopole, France)
Copyright: © 2005 |Pages: 40
DOI: 10.4018/978-1-59140-333-3.ch006
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Abstract

Biology has long inspired unconventional models of computation to computer scientists. This chapter focuses on a model inspired by biological development both at the molecular and cellular levels. Such biological processes are particularly interesting for computer science because the dynamic organization emerges from many decentralized and local interactions that occur concurrently at several time and space scales. Thus, they provide a source of inspiration to solve various problems related to mobility, distributed systems, open systems, etc. The fundamental mechanisms of biological development are now understood as changes within a complex dynamical system. This chapter advocates that these fundamental mechanisms, although mainly developed in a continuous framework, can be rephrased in a discrete setting relying on the notion of rewriting in a topological setting. The discrete formulation is as formal as the continuous one, enables the simulation, and opens a way to the systematic study of the behavioral properties of the biological systems. Directly inspired from these developmental processes, the chapter presents an experimental programming language called MGS. MGS is dedicated to the modeling and simulation of dynamical systems with dynamical structures. The chapter illustrates the basic notions of MGS through several algorithmic examples and by sketching various biological models.

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Dedication
Table of Contents
Acknowledgments
Marian Gheorghe
Chapter 1
Gheorghe Paun
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Membrane Computing: Main Ideas, Basic Results, Applications
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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
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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
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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
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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
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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
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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
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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
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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
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About the Authors