On Modelling The Immune System as a Complex system

TL;DR

This paper models the immune system as an adaptive complex network with emergent properties, highlighting its small-world structure and threshold mechanisms that prevent autoimmunity, and discusses modeling approaches including cellular automata and PDEs.

Contribution

It proposes a new perspective on immune system modeling as a complex network with specific properties and discusses the balance between cellular automata and PDE models.

Findings

Immune system exhibits small-world network structure.

Threshold mechanisms help prevent autoimmunity.

Multiple effectors attack each antigen, stabilizing the system.

Abstract

We argue that immune system is an adaptive complex system. It is shown that it has emergent properties. Its network structure is of the small world network type. The network is of the threshold type, which helps in avoiding autoimmunity. It has the property that every antigen (e.g.virus or bacteria) is typically attacked by more than one effector. This stabilizes the equilibrium state. Modelling complex systems is discussed. Cellular automata (CA) type models are successful but there are much less analytic results about CA than about other less successful models e.g. partial differential equations (PDE). A compromise is proposed