Genomic DNA copy number aberrations are frequent in solid tumours although their underlying causes 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). Competitive results have been obtained using IFRAIS. A biological interpretation of the results, carried out using Gene Ontology, followed the statistical assessment and put in evidence interesting patterns that are currently under investigation.
Induction of fuzzy rules with artificial immune systems in acgh based er status breast cancer characterization / Menolascina, Filippo; Teixeira Alves, Roberto; Tommasi, Stefania; Chiarappa, Patrizia; Delgado, Myriam; Mastronardi, Giuseppe; Paradiso, Angelo; Freitas, Alex; Bevilacqua, Vitoantonio. - ELETTRONICO. - (2007), pp. 431-431. (Intervento presentato al convegno 9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 tenutosi a London, UK nel July 07-11, 2007) [10.1145/1276958.1277051].
Induction of fuzzy rules with artificial immune systems in acgh based er status breast cancer characterization
Giuseppe Mastronardi;Vitoantonio Bevilacqua
2007-01-01
Abstract
Genomic DNA copy number aberrations are frequent in solid tumours although their underlying causes 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). Competitive results have been obtained using IFRAIS. A biological interpretation of the results, carried out using Gene Ontology, followed the statistical assessment and put in evidence interesting patterns that are currently under investigation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
