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Modeling the topological organization of cellular processes.
Jean-Louis Giavitto1, Olivier Michel
1LaMI u.m.r. 8042 du CNRS, Université d'Evry Val d'Essone-GENOPOLE, Tour Evry-2, 523 Place des Terasses de l'Agora, 91000 Evry, France. giavitto@lami.univ-evry.fr
Bio Systems
|August 14, 2003
Summary
Modeling cells as dynamic systems requires new programming approaches. The MGS project developed an experimental language to simulate these complex biological systems, integrating structure and state evolution for better intracellular process modeling.
Area of Science:
- Computational Biology
- Systems Biology
- Theoretical Computer Science
Background:
- Cells function as dynamical systems with evolving structures, posing significant modeling challenges.
- Existing computational models struggle to jointly represent cell state and structural changes over time.
Purpose of the Study:
- To develop novel programming concepts for simulating dynamical systems with evolving structures.
- To introduce the MGS project's experimental programming language for integrative cell modeling.
Main Methods:
- MGS unifies computational mechanisms like CHAM, Lindenmayer systems, Paun systems, and cellular automata.
- It utilizes a 'transformation' concept based on topological organization to handle dynamical structure evolution.
- Spatially distributed biochemical networks are used as a case study for illustration.
Main Results:
- MGS enables specification of spatially localized computations on heterogeneous entities.
- The language facilitates modeling the spatial and temporal organization of intracellular processes.
- Demonstrates a unified approach to simulating complex biological dynamics.
Conclusions:
- The MGS language offers a powerful tool for simulating complex, dynamically structured biological systems.
- It addresses the challenges of integrative cell modeling by jointly evolving cell state and structure.
- Provides a foundation for advanced computational approaches in systems and computational biology.