Open AccessReview of the systems biology of the immune system using agent‐based models
Author(s) -
Shinde Snehal B.,
Kurhekar Manish P.
Publication year - 2018
Publication title -
iet systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.367
H-Index - 50
eISSN - 1751-8857
pISSN - 1751-8849
DOI - 10.1049/iet-syb.2017.0073
Subject(s) - immune system , mechanism (biology) , computer science , adaptation (eye) , systems biology , artificial immune system , computational biology , biology , artificial intelligence , neuroscience , immunology , philosophy , epistemology
The immune system is an inherent protection system in vertebrate animals including human beings that exhibit properties such as self‐organisation, self‐adaptation, learning, and recognition. It interacts with the other allied systems such as the gut and lymph nodes. There is a need for immune system modelling to know about its complex internal mechanism, to understand how it maintains the homoeostasis, and how it interacts with the other systems. There are two types of modelling techniques used for the simulation of features of the immune system: equation‐based modelling (EBM) and agent‐based modelling. Owing to certain shortcomings of the EBM, agent‐based modelling techniques are being widely used. This technique provides various predictions for disease causes and treatments; it also helps in hypothesis verification. This study presents a review of agent‐based modelling of the immune system and its interactions with the gut and lymph nodes. The authors also review the modelling of immune system interactions during tuberculosis and cancer. In addition, they also outline the future research directions for the immune system simulation through agent‐based techniques such as the effects of stress on the immune system, evolution of the immune system, and identification of the parameters for a healthy immune system.