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Biological applications of knowledge graph embedding models
(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 ...
Knowledge graph driven approach to represent video streams for spatiotemporal event pattern matching in complex event processing
(World Scientific Publishing, 2020)
Complex Event Processing (CEP) is an event processing paradigm to perform real-time analytics over streaming data and match high-level event patterns. Presently, CEP is limited to process structured data stream. Video ...
Synergy between embedding and protein functional association networks for drug label prediction using harmonic function
(ACM and IEEE, 2020-10-16)
Semi-Supervised Learning (SSL) is an approach to machine learning that makes use of unlabeled data for training with a small amount of labeled data. In the context of molecular biology and pharmacology, one can take advantage ...