Learning Association Rules for Pharmacogenomic Studies

  • Giuseppe Agapito
  • Pietro H. Guzzi
  • Mario Cannataro
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10785)


The better understanding of variants of the genomes may improve the knowledge on the causes of the individuals’ different responses to drugs. The Affymetrix DMET (Drug Metabolizing Enzymes and Transporters) microarray platform offers the possibility to determine the gene variants of a patient and correlate them with drug-dependent adverse events. The analysis of DMET data is a growing research area. Existing approaches span from the use of simple statistical tests to more complex strategies based, for instance, on learning association rules. To support the analysis, we developed GenotypeAnalytics, a RESTFul-based software service able to automatically extract association rules from DMET datasets. GenotypeAnalytics is based on an optimised algorithm for learning rules that can outperform general purpose platforms.


Association rules Genomics SNP 



This work has been partially funded by the following research projects:

– “BA2Know-Business Analytics to Know” (PON03PE_00001_1), funded by the Italian Ministry of Education and Research (MIUR)

– INdAM - GNCS Project 2017: “Efficient Algorithms and Techniques for the Organization, Management and Analysis of Biological Big Data”.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Medical and Surgical SciencesUniversity Magna Græcia of CatanzaroCatanzaroItaly
  2. 2.Data Analytics Research CentreUniversity Magna Græcia of CatanzaroCatanzaroItaly

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