Jérémy Rivière, Pascal Ballet and Vincent Rodin.
NetBioDyn, a smart Agent-Based software to intuitively model and
simulate complex biological systems.
CCS 2016, the 2016 Conference on Complex Systems, Poster Session, Poster #253,
Amsterdam (Netherlands), 19-22 September 2016.
Abstract:
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.
[Riviere16a.pdf]