Cargando…
GESPA: classifying nsSNPs to predict disease association
BACKGROUND: Non-synonymous single nucleotide polymorphisms (nsSNPs) are the most common DNA sequence variation associated with disease in humans. Thus determining the clinical significance of each nsSNP is of great importance. Potential detrimental nsSNPs may be identified by genetic association stu...
Autores principales: | Khurana, Jay K., Reeder, Jay E., Shrimpton, Antony E., Thakar, Juilee |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4513380/ https://www.ncbi.nlm.nih.gov/pubmed/26206375 http://dx.doi.org/10.1186/s12859-015-0673-2 |
Ejemplares similares
-
Predicting deleterious nsSNPs: an analysis of sequence and structural attributes
por: Dobson, Richard J, et al.
Publicado: (2006) -
Prediction and Experimental Characterization of nsSNPs Altering Human PDZ-Binding Motifs
por: Gfeller, David, et al.
Publicado: (2014) -
coliSNP database server mapping nsSNPs on protein structures
por: Kono, Hidetoshi, et al.
Publicado: (2008) -
Investigation on the role of nsSNPs in HNPCC genes – a bioinformatics approach
por: Doss, C George Priya, et al.
Publicado: (2009) -
An ANN model for the identification of deleterious nsSNPs in tumor suppressor genes
por: Chandra, Vinod, et al.
Publicado: (2011)