Ontology guided data integration for computational prioritization of disease genes

  • Authors:

  • Bert Coessens;Stijn Christiaens;Ruben Verlinden;Yves Moreau;Robert Meersman;Bart De Moor

  • Affiliations:

  • Department of Electrical Engineering, Katholieke Universiteit Leuven;Semantics Technology and Applications Research Laboratory, Vrije Universiteit Brussel;Semantics Technology and Applications Research Laboratory, Vrije Universiteit Brussel;Department of Electrical Engineering, Katholieke Universiteit Leuven;Semantics Technology and Applications Research Laboratory, Vrije Universiteit Brussel;Department of Electrical Engineering, Katholieke Universiteit Leuven

  • Venue:
  • OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part I
  • Year:
  • 2006

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Abstract

In this paper we present our progress on a framework for collection and presentation of biomedical information through ontology-based mediation The framework is built on top of a methodology for computational prioritization of candidate disease genes, called Endeavour Endeavour prioritizes genes based on their similarity with a set of training genes while using a wide variety of information sources However, collecting information from different sources is a difficult process and can lead to non-flexible solutions In this paper we describe an ontology-based mediation framework for efficient retrieval, integration, and visualization of the information sources Endeavour uses The described framework allows to (1) integrate the information sources on a conceptual level, (2) provide transparency to the user, (3) eliminate ambiguity and (4) increase efficiency in information display.