This paper presents an association discovery framework for proteins based on semantic annotations from biomedical literatures. An automatic ontology-based annotation method is used to create a semantic protein annotation knowledge base. A semantic reasoning service enables realisation reasoning on original annotations to infer more accurate associations. A case study on protein-disease association discovery on a real-world colorectal cancer dataset is presented.
|Number of pages||4|
|Journal||CEUR Workshop Proceedings|
|Publication status||Published - 2013|
- protein annotation
- semantic reasoning