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PMID: 12529706 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

A new web-based data mining tool for the identification of candidate genes for human genetic disorders.

European journal of human genetics : EJHG ·Vol. 11 ·No. 1 ·2003-01-00 ·Pages 57-63

van Driel MA, Cuelenaere K, Kemmeren PP, Leunissen JA, Brunner HG

Abstract

To identify the gene underlying a human genetic disorder can be difficult and time-consuming. Typically, positional data delimit a chromosomal region that contains between 20 and 200 genes. The choice then lies between sequencing large numbers of genes, or setting priorities by combining positional data with available expression and phenotype data, contained in different internet databases. This process of examining positional candidates for possible functional clues may be performed in many different ways, depending on the investigator's knowledge and experience. Here, we report on a new tool called the GeneSeeker, which gathers and combines positional data and expression/phenotypic data in an automated way from nine different web-based databases. This results in a quick overview of interesting candidate genes in the region of interest. The GeneSeeker system is built in a modular fashion allowing for easy addition or removal of databases if required. Databases are searched directly through the web, which obviates the need for data warehousing. In order to evaluate the GeneSeeker tool, we analysed syndromes with known genesis. For each of 10 syndromes the GeneSeeker programme generated a shortlist that contained a significantly reduced number of candidate genes from the critical region, yet still contained the causative gene. On average, a list of 163 genes based on position alone was reduced to a more manageable list of 22 genes based on position and expression or phenotype information. We are currently expanding the tool by adding other databases. The GeneSeeker is available via the web-interface (http://www.cmbi.kun.nl/GeneSeeker/).

MeSH Terms
Computational Biology/methods Databases, Genetic Databases, Nucleic Acid Gene Expression Genetic Diseases, Inborn/genetics Humans Internet Noonan Syndrome/genetics Software
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
van Driel Marc A
Centre for Molecular and Biomolecular Informatics, University of Nijmegen, The Netherlands. M.vanDriel@cmbi.kun.nl
Cuelenaere Koen
Kemmeren Patrick P C W
Leunissen Jack A M
Brunner Han G
Article Info
Journal
European journal of human genetics : EJHG
Abbr.
Eur J Hum Genet
ISSN
1018-4813
Published
2003-01-00
Pages
57-63
Language
English
Region
England
NLM ID
9302235
Subset
IM
Analysis Services
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