COMPLEX BIOLOGICAL IMMUNE SYSTEM THROUGH THE EYES OF DUAL-PHASE EVOLUTION

Authored by Snehal B Shinde, Manish P Kurhekar

Date Published: 2018

DOI: 10.1142/s0218339018500213

Sponsors: No sponsors listed

Platforms: R

Model Documentation: Other Narrative Flow charts

Model Code URLs: https://sites.google.com/site/dpeimmunesystem/

Abstract

Dual-phase evolution (DPE) and the network theory help to analyze prominent properties of the complex adaptive systems (CASs) such as emergence and self-organization that are caused due to the phase transitions. These transitions are observed because of the increase and decrease in the number of system components and their interactions. The immune system, which is one of the CASs, provides an adaptive response to the foreign molecules. Prior to this response, the immune system is present in the circulation state and during the response, it moves into the growth state, where the number of immune cells and their cell cell contacts increase rapidly. The phase transitions from the circulation state to the growth state and then back to the circulation state cause the emergence and self-organization of the immune system, respectively. There is a need to understand these complex cellular dynamics during the immune response. In this paper, we have proposed an integrated model of DPE, network theory, and the immune system that has helped to understand and analyze the phases and properties of the immune system. Analysis of the growth phase network is provided and it is concluded that this network exhibits scale-free nature following power law for the degree distribution of nodes.

Tags

Agent-based models behavior Immune system connectivity Complex adaptive systems Dynamics networks Network theory Organization Transition Dual phase evolution