Now showing items 1-3 of 3

    • Biological applications of knowledge graph embedding models 

      Mohamed, Sameh K.; Nounu, Aayah; Nováček, Vít (Oxford University Press (OUP), 2020-02-17)
      Complex biological systems are traditionally modelled as graphs of interconnected biological entities. These graphs, i.e. biological knowledge graphs, are then processed using graph exploratory approaches to perform different ...
    • Discovering protein drug targets using knowledge graph embeddings 

      Mohamed, Sameh K .; Nováček, Vít; Nounu, Aayah (Oxford University Press, 2019-08-01)
      Motivation Computational approaches for predicting drug-target interactions (DTIs) can provide valuable insights into the drug mechanism of action. DTI predictions can help to quickly identify new promising (on-target) ...
    • Link prediction using multi part embeddings 

      Mohamed, Sameh K.; Nováček, Vít (NUI Galway, 2019-06-02)
      Knowledge graph embeddings models are widely used to provide scalable and efficient link prediction for knowledge graphs. They use different techniques to model embeddings interactions, where their tensor factorisation ...