Exploring the pharmacogenomics knowledge base (pharmgkb) for repositioning breast cancer drugs by leveraging Web ontology language (owl) and cheminformatics approaches

Qian Zhu, Cui Tao, Feichen Shen, Christopher G. Chute

Research output: Contribution to journalConference article


Computational drug repositioning leverages computational technology and high volume of biomedical data to identify new indications for existing drugs. Since it does not require costly experiments that have a high risk of failure, it has attracted increasing interest from diverse fields such as biomedical, pharmaceutical, and informatics areas. In this study, we used pharmacogenomics data generated from pharmacogenomics studies, applied informatics and Semantic Web technologies to address the drug repositioning problem. Specifically, we explored PharmGKB to identify pharmacogenomics related associations as pharmacogenomics profiles for US Food and Drug Administration (FDA) approved breast cancer drugs. We then converted and represented these profiles in Semantic Web notations, which support automated semantic inference. We successfully evaluated the performance and efficacy of the breast cancer drug pharmacogenomics profiles by case studies. Our results demonstrate that combination of pharmacogenomics data and Semantic Web technology/Cheminformatics approaches yields better performance of new indication and possible adverse effects prediction for breast cancer drugs.

Original languageEnglish (US)
Pages (from-to)172-182
Number of pages11
JournalPacific Symposium on Biocomputing
StatePublished - Jan 1 2014
Event19th Pacific Symposium on Biocomputing, PSB 2014 - Kohala Coast, United States
Duration: Jan 3 2014Jan 7 2014

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computational Theory and Mathematics

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