Bio-medical entity prioritisation based on literature with Semantic Web annotations

Summary An extension of the General and Rapid Association Study Engine (GRASE), aS emantic Web data (entity) prioritisation engine, is discussed. The GRASE employs a unique mechanism to prioritise entities using entitydocument relations by computing the statistical significance between entities and user keywords based on the number of related documents. We describe an improvement of prioritisation accuracy and connectivity to the Semantic Web using PubAnnotation.