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Selected Publication:
SHR Neuro Cancer Cardio Lipid Metab Microb
Baumgartner, C; Mátyás, G; Steinmann, B; Eberle, M; Stein, JI; Baumgartner, D.
A bioinformatics framework for genotype-phenotype correlation in humans with Marfan syndrome caused by FBN1 gene mutations.
J Biomed Inform. 2006; 39(2):171-183
Doi: 10.1016/j.jbi.2005.06.001
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- Co-authors Med Uni Graz
- Baumgartner Daniela
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- 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.
- Find related publications in this database (using NLM MeSH Indexing)
- Computational Biology - methods
- DNA Mutational Analysis - methods
- Database Management Systems -
- Databases, Genetic -
- Europe - epidemiology
- Fibrillin-1 -
- Fibrillins -
- Genotype -
- Humans -
- Marfan Syndrome - diagnosis
- Marfan Syndrome - epidemiology
- Marfan Syndrome - genetics
- Microfilament Proteins - genetics
- Phenotype -
- Find related publications in this database (Keywords)
- FBN1 gene
- Marfan syndrome
- similarity query processing
- data mining
- genotype-phenotype correlation