Fuzzy rule induction and artificial immune systems in female breast cancer familiarity profiling

Issue title: Recent Advances in Intelligent Paradigms Fusion and Their Applications

Guest editors: L.C. Jain, C.P. Lim and N.T. Nguyen

Article type: Research Article

Authors: Menolascina, Filippo^{a; *} | Alves, Roberto T.^c | Tommasi, Stefania^b | Chiarappa, Patrizia^b | Delgado, Myriam^c | Bevilacqua, Vitoantonio^a | Mastronardi, Giuseppe^a | Freitas, Alex A.^d | Paradiso, Angelo^b

Affiliations: [a] Department of Electronics and Electrical Engineering, Polytechnic of Bari, 2 Via E. Orabona 4, 70125. Bari, Italy | [b] Clinical and Experimental Oncology Laboratory – NCI, 1 Via Hahnemann 10, 70126. Bari, Italy | [c] Federal Technological University of Paraná – UTFPR, Av. 7 de setembro, 3165. Curitiba, Brazil | [d] Computing Laboratory – University of Kent, CT2 7NF. Canterbury, UK

Correspondence: [*] Corresponding author

Abstract: Genomic DNA copy number aberrations are frequent in solid tumours although their underlying causes of chromosomal instability in tumours remain obscure. In this paper we show how Artificial Immune System (AIS) paradigm can be successfully employed in the elucidation of biological dynamics of cancerous processes using a novel fuzzy rule induction system for data mining (IFRAIS) of aCGH data. Competitive results have been obtained using IFRAIS. A biological interpretation of the results carried out using Gene Ontology is currently under investigation.

DOI: 10.3233/HIS-2008-5306

Journal: International Journal of Hybrid Intelligent Systems, vol. 5, no. 3, pp. 161-165, 2008