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Bioinformatics Advance Access published online on November 27, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn612
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Gene-Disease Relationship Discovery based on Model-driven Data Integration and Database View Definition

S Yilmaz 1, P Jonveaux 1, C Bicep , L Pierron , M Smaïl-Tabbone and MD Devignes *

LORIA UMR7503, CNRS, INRIA, Nancy-Université, BP239, 54506 Vandoeuvre-les-Nancy cedex
1Laboratory for Human Genetics, Nancy Medical Faculty, rue du Morvan, 54500 Vandoeuvre-les-Nancy cedex.

*To whom correspondence should be addressed. Marie-Dominique Devignes, E-mail: devignes{at}loria.fr


  Abstract

Motivation: Computational methods are widely used to discover gene-disease relationships hidden in vast masses of available genomic and post-genomic data. In most current methods, a similarity measure is calculated between gene annotations and known disease genes or disease descriptions. However, more explicit gene-disease relationships are required for better insights into the molecular bases of diseases, especially for complex multi-gene diseases.

Results: Explicit relationships between genes and diseases are formulated as candidate gene definitions that may include intermediary genes, e.g., orthologous or interacting genes. These definitions guide data modelling in our database approach for gene-disease relationship discovery and are expressed as views which ultimately lead to the retrieval of documented sets of candidate genes. A system called ACGR (Approach for Candidate Gene Retrieval) has been implemented and tested with three case-studies including a rare orphan gene disease.

Availability: The ACGR sources are freely available at http://bioinfo.loria.fr/projects/acgr/acgr-software/.

Contact: devignes{at}loria.fr

Supplementary information: See the file "disease_description" and the folders "Xcollect_scenarios" and "ACGR_views" at http://bioinfo.loria.fr/projects/acgr .

Associate Editor: Dr. Alex Bateman

Received on July 1, 2008; revised on November 20, 2008; accepted on November 21, 2008

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