GraphGONet: a self-explaining neural network encapsulating the Gene Ontology graph for phenotype prediction on gene expression.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Medical care is becoming more and more specific to patients' needs due to the increased availability of omics data. The application to these data of sophisticated machine learning models, in particular deep learning (DL), can improve the field of precision medicine. However, their use in clinics is limited as their predictions are not accompanied by an explanation. The production of accurate and intelligible predictions can benefit from the inclusion of domain knowledge. Therefore, knowledge-based DL models appear to be a promising solution.

Authors

  • Victoria Bourgeais
    IBISC, Univ Evry, Université Paris-Saclay, 91020, Évry-Courcouronnes, France. victoria.bourgeais@univ-evry.fr.
  • Farida Zehraoui
    IBISC - IBGBI, University of Evry, 91037 Evry CEDEX, France.
  • Blaise Hanczar
    IBISC, Univ Evry, Université Paris-Saclay, 23 boulevard de France, 91034, Evry, France. blaise.hanczar@ibisc.univ-evry.fr.