Organization and evolution of synthetic idiotypic networks

TL;DR

This paper models idiotypic immune networks using weighted graphs with bit-strings, revealing topological features like small-world properties and scaling laws, and explores how aging affects network percolation.

Contribution

It introduces a novel graph-based model with biased bit-strings to mimic immune network topology and dynamics, including aging effects.

Findings

Weighted graphs exhibit small-world features.

Degree distributions show fringes consistent with experiments.

Aging can induce mild percolation phenomena.

Abstract

We introduce a class of weighted graphs whose properties are meant to mimic the topological features of idiotypic networks, namely the interaction networks involving the B-core of the immune system. Each node is endowed with a bit-string representing the idiotypic specificity of the corresponding B cell and a proper distance between any couple of bit-strings provides the coupling strength between the two nodes. We show that a biased distribution of the entries in bit-strings can yield fringes in the (weighted) degree distribution, small-worlds features, and scaling laws, in agreement with experimental findings. We also investigate the role of ageing, thought of as a progressive increase in the degree of bias in bit-strings, and we show that it can possibly induce mild percolation phenomena, which are investigated too.