Title
A bioinformatics framework for genotype-phenotype correlation in humans with Marfan syndrome caused by FBN1 gene mutations.
Abstract
Mutations in the human FBN1 gene are known to be associated with the Marfan syndrome, an autosomal dominant inherited multi-systemic connective tissue disorder. However, in the absence of solid genotype-phenotype correlations, the identification of an FBN1 mutation has only little prognostic value. We propose a bioinformatics framework for the mutated FBN1 gene which comprises the collection, management, and analysis of mutation data identified by molecular genetic analysis (DHPLC) and data of the clinical phenotype. To query our database at different levels of information, a relational data model, describing mutational events at the cDNA and protein levels, and the disease's phenotypic expression from two alternative views, was implemented. For database similarity requests, a query model which uses a distance measure based on log-likelihood weights for each clinical manifestation, was introduced. A data mining strategy for discovering diagnostic markers, classification and clustering of phenotypic expressions was provided which enabled us to confirm some known and to identify some new genotype-phenotype correlations.
Year
DOI
Venue
2006
10.1016/j.jbi.2005.06.001
Journal of Biomedical Informatics
Keywords
Field
DocType
fbn1 gene,fbn1 gene mutation,clinical manifestation,phenotypic expression,genotype–phenotype correlation,data mining strategy,fbni gene,fbni mutation,human fbni gene,data mining,relational data model,database similarity request,genotype-phenotype correlation,similarity query processing,mutation data,clinical phenotype,marfan syndrome,bioinformatics framework,autosomal dominant,molecular genetics,connective tissue
Genotype,Genetic analysis,Marfan syndrome,Gene,Phenotype,Computer science,Bioinformatics,Cluster analysis,Genetics,Dominance (genetics),Mutation
Journal
Volume
Issue
ISSN
39
2
1532-0480
Citations 
PageRank 
References 
1
0.47
3
Authors
6
Name
Order
Citations
PageRank
Christian Baumgartner110014.03
Gábor Mátyás210.47
Beat Steinmann310.47
Martin Eberle4191.69
Jörg I Stein510.47
Daniela Baumgartner6252.24