Artificial Immune Systems
[Introduction] - [Contacts] - [Research] - [Publications] - [Projects] - [Events] - [Teaching] - [The Giants].
Computational Immunology
The Natural Immune System (IS) has to assure recognition of each potentially
dangerous molecule or substance, generically called antigen
that can infect the host organism.
The IS first recognizes it as dangerous or extraneous and then
mounts a response to eliminate it.
To detect an antigen, the IS activates a recognition process.
Moreover, the IS only has finite resources and often very little time to produce antibodies
for each possible antigen.
Artificial Immune Systems
The new field of Artificial Immune Systems, (or Immunological Computation, Immune Algorithms,
Immune-based Systems) attempts to use methods and concepts from Immunology to design immunity-based system applications in science and engineering.
The Immune Algorithms (IAs) are complex adaptive systems in which
learning takes place by evolutionary mechanisms similar to biological evolution.
References
- V. Cutello, G. Nicosia, M. Pavone, I. Prizzi,
"Protein Multiple Sequence Alignment by Hybrid Bio-Inspired Algorithms",
Nucleic Acids Research - Oxford Journals, doi:10.1093/nar/gkq1052
(To Appear).
- V. Cutello, G. Nicosia, M. Pavone, J. Timmis,
"
An Immune Algorithm for Protein Structure Prediction on Lattice Models",
IEEE Transactions on Evolutionary Computation, 11(1):101-117, 2007.
- M. Castrogiovanni, G. Nicosia, R. Rascuna',
"
Experimental Analysis of the Aging Operator for Static and Dynamic Optimisation Problems",
11th Int. Conf. on Knowledge-Based and Intelligent Information and Engineering Systems - KES 2007,
12-14 September 2007, Vietri sul Mare, Italy.
Springer, LNCS 4694:804-811, 2007.
- V. Cutello, G. Nicosia, P. S. Oliveto, M. Romeo,
"
On the Convergence of Immune Algorithms",
The First IEEE Symp. on Foundations of Computational Intelligence, FOCI 2007,
1-5 April 2007, Honolulu, Hawaii, USA.
IEEE Press, pp. 409-415, 2007.
- G. Nicosia, V. Cutello, The Clonal Selection Principle for in Silico and in Vitro Computing,
book chapter in L. N. de Castro and F. J. Von Zuben (Eds), Recent Developments in Biologically Inspired Computing, 2004.
- F. Castiglione, S. Motta, G. Nicosia,
"
Pattern Recognition by primary and secondary response of an Artificial Immune System",
Theory in Biosciences, 120(2):93-106, 2001.
- F. Castiglione, G. Mannella, S. Motta, G. Nicosia, " A Network of Cellular Automata for the Simulation of the Immune System", Int. J. of Modern Physics C (Physics and Computers), 10(4):677-686, 1999.
[Introduction] - [Contacts] - [Research] - [Publications] - [Projects] - [Events] - [Teaching] - [The Giants].