Ontology-based knowledge discovery in pharmacogenomics

Adv Exp Med Biol. 2011;696:357-66. doi: 10.1007/978-1-4419-7046-6_36.

Abstract

One current challenge in biomedicine is to analyze large amounts of complex biological data for extracting domain knowledge. This work holds on the use of knowledge-based techniques such as knowledge discovery (KD) and knowledge representation (KR) in pharmacogenomics, where knowledge units represent genotype-phenotype relationships in the context of a given treatment. An objective is to design knowledge base (KB, here also mentioned as an ontology) and then to use it in the KD process itself. A method is proposed for dealing with two main tasks: (1) building a KB from heterogeneous data related to genotype, phenotype, and treatment, and (2) applying KD techniques on knowledge assertions for extracting genotype-phenotype relationships. An application was carried out on a clinical trial concerned with the variability of drug response to montelukast treatment. Genotype-genotype and genotype-phenotype associations were retrieved together with new associations, allowing the extension of the initial KB. This experiment shows the potential of KR and KD processes, especially for designing KB, checking KB consistency, and reasoning for problem solving.

MeSH terms

  • Acetates / pharmacology
  • Anti-Asthmatic Agents / pharmacology
  • Asthma / drug therapy
  • Asthma / genetics
  • Computational Biology
  • Data Interpretation, Statistical
  • Data Mining / statistics & numerical data
  • Databases, Genetic
  • Genetic Association Studies / statistics & numerical data
  • Humans
  • Knowledge Bases
  • Logistic Models
  • Pharmacogenetics / statistics & numerical data*
  • Quinolines / pharmacology

Substances

  • Acetates
  • Anti-Asthmatic Agents
  • Quinolines
  • montelukast