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Total: 6 results found.

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1. Identifying disease trajectories with predicate information from a knowledge graph
(Publication)
Created on 11 December 2020
2. Using predicate information from a knowledge graph to identify disease trajectories
(Publication)
Created on 11 December 2020
3. Drug prioritization using the semantic properties of a knowledge graph
(Publication)
Compounds that are candidates for drug repurposing can be ranked by leveraging knowledge available in the biomedical literature and databases. This knowledge, spread across a variety of sources, can be ...
Created on 11 December 2020
4. Using predicate and provenance information from a knowledge graph for drug efficacy screening
(Publication)
© 2018 The Author(s). Background: Biomedical knowledge graphs have become important tools to computationally analyse the comprehensive body of biomedical knowledge. They represent knowledge as subject-predicate-object ...
Created on 11 December 2020
5. Automated extraction of potential migraine biomarkers using a semantic graph
(Publication)
© 2017 The Author(s) Problem Biomedical literature and databases contain important clues for the identification of potential disease biomarkers. However, searching these enormous knowledge reservoirs and ...
Created on 11 December 2020
6. RELigator: Chemical-disease relation extraction using prior knowledge and textual information
(Publication)
The Erasmus MC team participated in the chemical-disease relation (CDR) task in the BioCreative V challenge. The CDR task consists of two subtask: automatic disease named entity recognition and normalization ...
Created on 16 November 2016
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