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.
['Jemma X. Wu', 'Edmond J. Breen', 'Xiaomin Song', 'Brett Cooke', 'Mark P. Molloy']
A protein annotation framework empowered with semantic reasoning