NetBioDyn, a smart Agent-Based software to intuitively model and simulate complex biological systems
Résumé
Modeling and teaching complex biological systems is a difficult process. The Multi-Agent paradigm has proved to be an appropriate approach, both in research and education, to grasp the complexity of these systems and investigating the underlying concepts of emergence and self-organization. As such, Agent-Based software are more and more used in life sciences to implement these models in virtual environments and simulate them. However, most of these software require knowledge and skills in programming languages, such as Java or the NetLogo environment. The gap between most of Agent-Based software prerequisites and the actual programming skills of (future) biologists has to be reduced and the processes of implementing a model and simulate it made more intuitive. To answer this issue, we propose a smart, intuitive and open-source software aimed at biologists (students, teachers, researchers) to easily build and simulate complex biological mechanisms observed in multicellular and molecular systems. Thanks to its specific graphical user interface guided by the Multi-Agent paradigm (entities, behaviors and interactions) NetBioDyn does not need any prerequisite or knowledge in computer programming. It thus allows users to create in a simple way bottom-up models where unexpected behaviors can emerge from simple reactive interacting entities, and test hypothesis by creating various simulations, while providing at any time a simplified and complete view of the system's state. NetBioDyn has been successfully used to investigate systems such as two marine bacteria involved in a predator-prey relationship or the blood coagulation mechanisms in a small section of a vein. Moreover, NetBioDyn tackles the well-known problem of calibrating a model with interdependent, interconnected parameters by including a self-adjusting Multi-Agent System. This tools aims to automatically find the proper values for all the parameters involved in a simulation (interactions’ probabilities, entities’ lifespan etc.) according to real results obtained for example in vitro.
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