Learning from biomedical linked data to suggest valid pharmacogenes.

Journal: Journal of biomedical semantics
Published Date:

Abstract

BACKGROUND: A standard task in pharmacogenomics research is identifying genes that may be involved in drug response variability, i.e., pharmacogenes. Because genomic experiments tended to generate many false positives, computational approaches based on the use of background knowledge have been proposed. Until now, only molecular networks or the biomedical literature were used, whereas many other resources are available.

Authors

  • Kevin Dalleau
    LORIA (CNRS, Inria Nancy-Grand Est, University of Lorraine), Campus Scientifique, Nancy, France.
  • Yassine Marzougui
    LORIA (CNRS, Inria Nancy-Grand Est, University of Lorraine), Campus Scientifique, Nancy, France.
  • Sébastien Da Silva
    LORIA (CNRS, Inria Nancy-Grand Est, University of Lorraine), Campus Scientifique, Nancy, France.
  • Patrice Ringot
    LORIA (CNRS, Inria Nancy-Grand Est, University of Lorraine), Campus Scientifique, Nancy, France.
  • Ndeye Coumba Ndiaye
    UMR U1122 IGE-PCV (INSERM, University of Lorraine), 30 Rue Lionnois, Nancy, France.
  • Adrien Coulet
    LORIA (CNRS, Inria Nancy-Grand Est, University of Lorraine), Campus Scientifique, Nancy, France. adrien.coulet@loria.fr.