An Evolutionary Immune Network for Data Clustering
SBRN '00 Proceedings of the VI Brazilian Symposium on Neural Networks (SBRN'00)
The affirmation of self: a new perspective on the immune system
Artificial Life
Properties of the bersini experiment on self-assertion
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Topological constraints in the evolution of idiotypic networks
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Analysis of a growth model for idiotypic networks
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
Tolerance vs intolerance: how affinity defines topology in an idiotypic network
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
Structural properties of shape-spaces
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
On the use of hyperspheres in artificial immune systems as antibody recognition regions
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
Not all balls are round: an investigation of alternative recognition-region shapes
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
Idiotypic Immune Networks in Mobile-Robot Control
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A survey on optimization metaheuristics
Information Sciences: an International Journal
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Many recent advances have been made in understanding the functional implications of the global topological properties of biological networks through the application of complex network theory, particularly in the area of small-world and scale-free topologies. Computational studies which attempt to understand the structure---function relationship usually proceed by defining a representation of cells and an affinity measure to describe their interactions. We show that this necessarily restricts the topology of the networks that can arise--furthermore, we show that although simple topologies can be produced via representation and affinity measures common in the literature, it is unclear how to select measures which result in complex topologies, for example, exhibiting scale-free functionality. In this paper, we introduce the concept of the potential network as a method in which abstract network topologies can be directly studied, bypassing any definition of shape-space and affinity function. We illustrate the benefit of the approach by studying the evolution of idiotypic networks on a selection of scale-free and regular topologies, finding that a key immunological property--tolerance--is promoted by bi-partite and heterogeneous topologies. The approach, however, is applicable to the study of any network and thus has implications for both immunology and artificial immune systems.