DMET-miner: Efficient learning of association rules from genotyping data for personalized medicine

Author

Guzzi, Pietro H. ; Agapito, Giuseppe ; Di Martino, Maria Teresa ; Arbitrio, Mariamena ; Tassone, Pierfrancesco ; Tagliaferri, Pierosandro ; Cannataro, Mario

Author_Institution

Dept. of Med. & Surg. Sci., Magna Graecia Univ., Catanzaro, Italy

fYear

2014

fDate

2-5 Nov. 2014

Firstpage

59

Lastpage

62

Abstract

Recent developments of microarray technology enable the investigation of allelic variants that may be correlated to phenotypes. In particular the Affymetrix DMET (Drug Metabolism Enzymes and Transporters) platform enables the simultaneous investigation of all the genes that are related to drug absorption, distribution, metabolism and excretion (ADME) and it has been used in clinical studies. In a previous work we developed DMET-Analyzer, a platform able to automatize the study of allelic variants, that has been validated in clinical studies. DMET-Analyzer is able to correlate a single variant for each probe (related to a portion of a gene) through the use of the Fisher test, on the other hand it is unable to discover multiple associations among allelic variants. To overcome those limitations, here we propose DMET-Miner, that is able to correlate the presence of a set of allelic variants by employing an Apriori-like discovery strategy. Preliminary experiments on a synthetic DMET dataset.

Keywords

biochemistry; bioinformatics; data mining; drugs; enzymes; genetics; genomics; molecular biophysics; Affymetrix DMET platform; Apriori-like discovery strategy; DMET-Analyzer; DMET-Miner; Fisher test; allelic variants; association rules; drug absorption; drug distribution; drug excretion; drug metabolism; drug metabolism enzymes-and-transporters; efficient learning; genotyping data; microarray technology; personalized medicine; synthetic DMET dataset; Association rules; Biochemistry; Bioinformatics; Drugs; Itemsets; Probes; Association Rules; Clinical Bioinformatics; Itemset Mining; SNP (Single Nucleotide Polymorphism);

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on

Conference_Location

Belfast

Type

conf

DOI

10.1109/BIBM.2014.6999127

Filename

6999127