A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed records

BACKGROUND: Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile...

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Detalles Bibliográficos
Autores principales: Jiang, Li, Edwards, Stefan M, Thomsen, Bo, Workman, Christopher T, Guldbrandtsen, Bernt, Sørensen, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4181406/
https://www.ncbi.nlm.nih.gov/pubmed/25253562
http://dx.doi.org/10.1186/1471-2105-15-315

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4181406/
https://www.ncbi.nlm.nih.gov/pubmed/25253562
http://dx.doi.org/10.1186/1471-2105-15-315

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