Linked Life Data

12385992

Source:http://linkedlifedata.com/resource/pubmed/id/12385992

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2002-10-18
pubmed:abstractText
MOTIVATION: A method for prediction of disease relevant human genes from the phenotypic appearance of a query disease is presented. Diseases of known genetic origin are clustered according to their phenotypic similarity. Each cluster entry consists of a disease and its underlying disease gene. Potential disease genes from the human genome are scored by their functional similarity to known disease genes in these clusters, which are phenotypically similar to the query disease. RESULTS: For assessment of the approach, a leave-one-out cross-validation of 878 diseases from the OMIM database, using 10672 candidate genes from the human genome, is performed. Depending on the applied parameters, in roughly one-third of cases the true solution is contained within the top scoring 3% of predictions and in two-third of cases the true solution is contained within the top scoring 15% of predictions. The prediction results can either be used to identify target genes, when searching for a mutation in monogenic diseases or for selection of loci in genotyping experiments in genetically complex diseases.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1367-4803
pubmed:author
pubmed:issnType
Print
pubmed:volume
18 Suppl 2
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S110-5
pubmed:dateRevised
2009-11-19
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
A similarity-based method for genome-wide prediction of disease-relevant human genes.
pubmed:affiliation
Institute of Human Genetics, Bonn University Hospital, Germany. jan.freudenberg@uni-bonn.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Evaluation Studies