AGENT-BASED MODELLING FOR SYSTEMS BIOLOGY

Why ABM?

Biological systems are complex adaptive systems (CAS). Complex systems are composed of many components that interact dynamically so that the system shows spontaneous self-organisation to produce global, emergent structures and behaviours. In biology, the nature of the interactions themselves are often state- or context-dependent so that systems are adaptive. A 'taxonomy of complexity' suggested by (Mitchell, 2003) captures well the complexity found in Biology:

Constitutive Complexity: Organisms display complexity in structure, the whole is made up of numerous parts in non-random organisation.
Dynamic Complexity: Organisms are complex in their functional processes.
Evolved Complexity: Alternative evolutionary solutions adaptive problems, historically contingent.

Agent-Based Modelling (ABM) offers a flexible and intuitive framework for coping with all these types of complexity, since:

Constitutive Complexity: The structure of the system can be specified both by placing constraints on the system as a whole (top-down) or by specifying the organisation of entities individually (bottom-up). This gives the maximum degree of control over the system's structure.
Dynamic Complexity: Entity instances can be separated from their function and behaviour. This addresses the context- and time-dependent nature of biological function. A biological entity can be represented as participating in multiple pathways and processes at different times or in different environments.
Evolved Complexity: Both system and entity behaviour can be dependent on a unique history because entities have unique identities. History-dependent behaviours can also interact with one another to produce new sets of behaviours. The history of an entity forms part of the system's history which in turn feeds back to determine the entity's current behaviour.

In addition, MAS are inherently compositional in structure so that multiple models, including non-AB models, can be integrated in the same framework and multiple scales can be incorporated into the same model.

References:

Mitchell, S. D. (2003). Biological Complexity and Integrative Pluralism. Cambridge, Cambrige University Press.