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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
biochemistry, genetics and molecular biology
Integration of text- and data-mining using ontologies successfully selects disease gene candidates
Nucleic Acids Research, Volume 33, No. 5, Year 2005
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Description
Genome-wide techniques such as microarray analysis, Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS), linkage analysis and association studies are used extensively in the search for genes that cause diseases, and often identify many hundreds of candidate disease genes. Selection of the most probable of these candidate disease genes for further empirical analysis is a significant challenge. Additionally, identifying the genes that cause complex diseases is problematic due to low penetrance of multiple contributing genes. Here, we describe a novel bioinformatic approach that selects candidate disease genes according to their expression profiles. We use the eVOC anatomical ontology to integrate text-mining of biomedical literature and data-mining of available human gene expression data. To demonstrate that our method is successful and widely applicable, we apply it to a database of 417 candidate genes containing 17 known disease genes. We successfully select the known disease gene for 15 out of 17 diseases and reduce the candidate gene set to 63.3% (±18.8%) of its original size. This approach facilitates direct association between genomic data describing gene expression and information from biomedical texts describing disease phenotype, and successfully prioritizes candidate genes according to their expression in disease-affected tissues. © The Author 2005. Published by Oxford University Press. All rights reserved.
Authors & Co-Authors
Tiffin, Nicki T.
South Africa, Bellville
University of the Western Cape
Kelso, Janet F.
South Africa, Bellville
University of the Western Cape
Germany, Leipzig
Max-planck-institut Für Evolutionäre Anthropologie
Powell, Alan R.
South Africa, Bellville
University of the Western Cape
Pan, Hong
Singapore, Singapore City
A-star, Institute for Infocomm Research
Bajic, Vladimir B.
Singapore, Singapore City
A-star, Institute for Infocomm Research
Hide, Winston A.
South Africa, Bellville
University of the Western Cape
Statistics
Citations: 228
Authors: 6
Affiliations: 3
Identifiers
Doi:
10.1093/nar/gki296
ISSN:
03051048
e-ISSN:
13624962
Research Areas
Environmental
Genetics And Genomics