Now showing items 1-3 of 3

    • 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) ...
    • A random walk model for entity relatedness 

      Torres-Tramón, Pablo; Hayes, Conor (Springer Verlag, 2018-10-31)
      Semantic relatedness is a critical measure for a wide variety of applications nowadays. Numerous models, including path-based, have been proposed for this task with great success in many applications during the last few ...
    • Toward distributed, global, deep learning using IoT devices 

      Sudharsan, Bharath; Patel, Pankesh; Breslin, John; Ali, Muhammad Intizar; Mitra, Karan; Dustdar, Schahram; Rana, Omer; Jayaraman, Prem Prakash; Ranjan, Rajiv (Institute of Electrical and Electronics Engineers (IEEE), 2021-07-20)
      Deep learning (DL) using large scale, high-quality IoT datasets can be computationally expensive. Utilizing such datasets to produce a problem-solving model within a reasonable time frame requires a scalable distributed ...