By D. Dasgupta, K. KrishnaKumar, D. Wong, M. Berry (auth.), Giuseppe Nicosia, Vincenzo Cutello, Peter J. Bentley, Jon Timmis (eds.)
Arti?cial Immune platforms have come of age. they're not an vague computersciencetechnique,workedonbyacoupleoffarsightedresearchgroups. this day, researchers around the globe are engaged on new machine algorithms encouraged through the workings of the immune process. This lively ?eld of analysis investigates how immunobiology may also help our expertise, and alongside the best way is commencing to support biologists comprehend their particular difficulties. AIS is now sufficiently old to appreciate its roots, its context within the study group, and its fascinating destiny. It has grown too sizeable to be con?ned to s- cial periods in evolutionary computation meetings. AIS researchers are actually forming their very own neighborhood and identification. The foreign convention on Arti?cial Immune platforms is proud to be the ultimate convention within the sector. As its organizers, we have been commemorated to have this sort of number of leading edge and unique scienti?c papers provided this 12 months. ICARIS 2004 was once the 3rd foreign convention committed completely to the ?eld of Arti?cial Immune structures (AIS). It used to be held in Catania, at the appealing island of Sicily, Italy, in the course of September 13–16, 2004. whereas internet hosting the convention, the town of Catania gave the members the chance to benefit from the richness of its old and cultural surroundings and the wonderful thing about its ordinary assets, the ocean, and the Etna volcano.
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Extra resources for Artificial Immune Systems: Third International Conference, ICARIS 2004, Catania, Sicily, Italy, September 13-16, 2004. Proceedings
11. 12. 13. 14. B. N. J. N. , “The Clonal Selection Algorithm with Engineering Applications”, GECCO’00 Proc. of the Genetic and Evolutionary Computation Conference – Workshop Proceedings, pp. 36-37, 2000a. de Castro, L. N. & Von Zuben, F. , “An Evolutionary Immune Network for Data Clustering”, Proc. of IEEE SBRN – Brazilian Symposium on Neural Networks, pp. 84-89, 2000b. , “Cluster Analysis and Display of Genome-wide Expression Patterns”, Proc. Natl. Acad. 95, pp. 14863-14868, USA, 1998. , Landau, S.
This kind of interpretation is not provided by other methods found in the literature, and it can be very relevant to gene expression data analysis. References 1. 2. 3. B. , “Bioinformatics Data Analysis Using an Artificial Immune Network”, Lecture Notes in Computer Sciences, Proc. 22-33, Edinburgh, UK, 2003. de Castro, L. N. & Timmis, J. , “Hierarchy and Convergence of Immune Networks: Basic Ideas and Preliminary Results”, Proc. First International Conference, ICARIS 2002, pp. 231-240, 2002. de Castro, L.
7. 8. 9. 10. 11. 12. 13. 14. B. N. J. N. , “The Clonal Selection Algorithm with Engineering Applications”, GECCO’00 Proc. of the Genetic and Evolutionary Computation Conference – Workshop Proceedings, pp. 36-37, 2000a. de Castro, L. N. & Von Zuben, F. , “An Evolutionary Immune Network for Data Clustering”, Proc. of IEEE SBRN – Brazilian Symposium on Neural Networks, pp. 84-89, 2000b. , “Cluster Analysis and Display of Genome-wide Expression Patterns”, Proc. Natl. Acad. 95, pp. 14863-14868, USA, 1998.