An Agent-oriented Conceptual Framework for Biological Systems Simulation

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. On the one hand, researchers working on Systems Biology aim to understand how living systems perform routinely complex tasks. On the other, people involved in Pharmacogenomics strive to study how an individual's genetic inheritance affects the body's response to drugs. Research in all the above disciplines requires the ability to simulate particular biological processes (i.e. metabolic pathways) which characterize biological systems as cells, organs, organisms and communities. Biological processes are complex systems, i.e. a set of components that interacts with each other and with an external dynamic environment.

In this work, we aim to provide an alternative way to specify complex systems based on behavioral modelling. We consider a biological process as an activity-based application performed by actors in a dynamic and sometime unpredictable environment; each actor plays his role in relation to the process it is involved, but in general they are part of a more complex system. We propose a conceptual framework to engineering an agent society which simulate the behavior of a biological process. The agents society and its social rules are described through a coordination model specified for a biological process with semiformal languages based on System Biology Modelling Languages for the static-structural and functional views and on UML-like diagrams for the dynamic (control flow) behavior.