Architecture of idiotypic networks: Percolation and scaling Behavior

Architecture of idiotypic networks: Percolation and scaling Behavior

We investigate a model where idiotypes (characterizing B lymphocytes and antibodies of an immune system) and anti-idiotypes are represented by complementary bit strings of a given length d allowing for a number of mismatches (matching rules). In this model, the vertices of the hypercube in dimension d represent the potential repertoire of idiotypes. A random set of (with probability p) occupied vertices corresponds to the expressed repertoire of idiotypes at a given moment. Vertices of this set linked by the above matching rules build random clusters. We give a structural and statistical characterization of these clusters, or in other words of the architecture of the idiotypic network. Increasing the probability p one finds at a critical p a percolation transition where for the first time a large connected graph occurs with probability 1. Increasing p further, there is a second transition above which the repertoire is complete in the sense that any newly introduced idiotype finds a complementary anti-idiotype. We introduce structural characteristics such as the mass distribution and the fragmentation rate for random clusters, and determine the scaling behavior of the cluster size distribution near the percolation transition, including finite size corrections. We find that slightly above the percolation transition the large connected cluster (the central part of the idiotypic network) consists typically of one highly connected part and a number of weakly connected constituents and coexists with a number of small, isolated clusters. This is in accordance with the picture of a central and a peripheral part of the idiotypic network and gives some support to idealized architectures of the central part used in recent dynamical mean field models.

Brede, Markus

bbd03865-8e0b-4372-b9d7-cd549631f3f7

Behn, Ulrich

878cca24-03dd-4682-be65-86e075bfc839

2001

Brede, Markus

bbd03865-8e0b-4372-b9d7-cd549631f3f7

Behn, Ulrich

878cca24-03dd-4682-be65-86e075bfc839

Brede, Markus and Behn, Ulrich
(2001)
Architecture of idiotypic networks: Percolation and scaling Behavior.
*Physical Review E*, 64 (1).

## Abstract

We investigate a model where idiotypes (characterizing B lymphocytes and antibodies of an immune system) and anti-idiotypes are represented by complementary bit strings of a given length d allowing for a number of mismatches (matching rules). In this model, the vertices of the hypercube in dimension d represent the potential repertoire of idiotypes. A random set of (with probability p) occupied vertices corresponds to the expressed repertoire of idiotypes at a given moment. Vertices of this set linked by the above matching rules build random clusters. We give a structural and statistical characterization of these clusters, or in other words of the architecture of the idiotypic network. Increasing the probability p one finds at a critical p a percolation transition where for the first time a large connected graph occurs with probability 1. Increasing p further, there is a second transition above which the repertoire is complete in the sense that any newly introduced idiotype finds a complementary anti-idiotype. We introduce structural characteristics such as the mass distribution and the fragmentation rate for random clusters, and determine the scaling behavior of the cluster size distribution near the percolation transition, including finite size corrections. We find that slightly above the percolation transition the large connected cluster (the central part of the idiotypic network) consists typically of one highly connected part and a number of weakly connected constituents and coexists with a number of small, isolated clusters. This is in accordance with the picture of a central and a peripheral part of the idiotypic network and gives some support to idealized architectures of the central part used in recent dynamical mean field models.

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## More information

Published date: 2001

Organisations:
Agents, Interactions & Complexity

## Identifiers

Local EPrints ID: 272895

URI: https://eprints.soton.ac.uk/id/eprint/272895

ISSN: 1063-651X

PURE UUID: 771740c5-6b94-47c7-af9b-c73ee95e42d4

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Date deposited: 29 Sep 2011 16:37

Last modified: 01 Nov 2017 05:36

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## Contributors

Author:
Ulrich Behn

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