Discovery of Genes Implied in Cancer by Genetic Algorithms and Association Rules

  • Alejandro Sánchez Medina
  • Alberto Gil Pichardo
  • Jose Manuel García-Heredia
  • María Martínez-BallesterosEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9648)


This work proposes a methodology to identify genes highly related with cancer. In particular, a multi-objective evolutionary algorithm named CANGAR is applied to obtain quantitative association rules. This kind of rules are used to identify dependencies between genes and their expression levels. Hierarchical cluster analysis, fold-change and review of the literature have been considered to validate the relevance of the results obtained. The results show that the reported genes are consistent with prior knowledge and able to characterize cancer colon patients.


Data mining Association rules Gene expression Cancer 



The financial support from the Spanish Ministry of Science and Technology, projects TIN2011-28956-C02-02 and TIN2014-55894-C2-1-R, and from the Junta de Andalucia, P11-TIC-7528 and P12-TIC-1728, is acknowledged.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Alejandro Sánchez Medina
    • 1
  • Alberto Gil Pichardo
    • 1
  • Jose Manuel García-Heredia
    • 2
  • María Martínez-Ballesteros
    • 3
    Email author
  1. 1.University of SevillaSevilleSpain
  2. 2.Department of Vegetal Biochemistry and Molecular BiologyUniversity of SevilleSevilleSpain
  3. 3.Department of Computer ScienceUniversity of SevilleSevilleSpain

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