Computational Challenges in Cell Simulation: A Software Engineering Approach
IEEE Intelligent Systems
Uses of Multiagents Systems for Simulation of MAPK Pathway
BIBE '03 Proceedings of the 3rd IEEE Symposium on BioInformatics and BioEngineering
Theoretical Computer Science - Special issue: Computational systems biology
Designing multi-agent systems: a framework and application
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
A Reverse Engineering Form for Multi Agent Systems
Engineering Societies in the Agents World IX
Adaptive modularization of the MAPK signaling pathway using the multiagent paradigm
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
IODA: an interaction-oriented approach for multi-agent based simulations
Autonomous Agents and Multi-Agent Systems
Combinatorial optimization in Biology using Probability Collectives Multi-agent Systems
Expert Systems with Applications: An International Journal
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The advent of the computer and computer science, and in particular virtual reality, offers new experiment possibilities with numerical simulations and introduces a new type of investigation for the complex systems study: the in virtuo experiment. This work lies on the framework of multi-agent systems. We propose a generic model for systems biology based on reification of the interactions, on a concept of organization and on a multi-model approach. By 'reification' we understand that interactions are considered as autonomous agents. The aim has been to combine the systemic paradigm and the virtual reality to provide an application able to collect, simulate, experiment and understand the knowledge owned by different biologists working around an interdisciplinary subject. Here, we have been focused on the urticaria disease understanding. Autonomy is taken as a principle. The method permits to integrate different natures of model in the same application using chaotic asynchronous iterations and C++ library: AReVi. We have modeled biochemical reactions, molecular 3D diffusion, cell organizations and mechanical 3D interactions. It also permits to embed different expert system modeling methods like fuzzy cognitive maps. This work provides a toolbox easily adaptable to new biological studies.