Abstract
In this paper we examine the impact of graph theory and more particularly the scale-free topology on Immune Network models. In the case of a simple but not trivial model we analyze network performances as long term selectivity properties, its computational capabilities as memory capacity, and relation with Neural Networks. A more advanced Immune Network model is conceptualized and it is developed a scaffold for further mathematical investigation.
| Original language | English |
|---|---|
| Pages (from-to) | 93-101 |
| Number of pages | 9 |
| Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Volume | 2787 |
| Publication status | Published - 2003 |
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ASJC Scopus subject areas
- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science
Cite this
Tieri, P., Valensin, S., Franceschi, C., Morandi, C., & Castellani, G. C. (2003). Memory and selectivity in evolving scale-free immune networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2787, 93-101.