Induction of fuzzy rules with artificial immune systems in acgh based er status breast cancer characterization

Filippo Menolascina, Roberto Teixeira Alves, Stefania Tommasi, Patrizia Chiarappa, Myriam Delgado, Giuseppe Mastronardi, Angelo Paradiso, Alex Freitas, Vitoantonio Bevilacqua

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationProceedings of GECCO 2007: Genetic and Evolutionary Computation Conference
Pages431
Number of pages1
DOIs
Publication statusPublished - 2007
Event9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 - London, United Kingdom
Duration: Jul 7 2007Jul 11 2007

Other

Other9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
CountryUnited Kingdom
CityLondon
Period7/7/077/11/07

Keywords

  • ACGH
  • AIS
  • Breast cancer
  • Data mining
  • Fuzzy rules induction
  • IFRAIS

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science

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