nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms | Zendy

Li Bao | Zendy; Mi Zhou | Zendy; Yan Cui | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms

Author(s) -

Li Bao,

Mi Zhou,

Yan Cui

Publication year - 2005

Publication title -

nucleic acids research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 9.008

H-Index - 537

eISSN - 1362-4954

pISSN - 0305-1048

DOI - 10.1093/nar/gki372

Subject(s) - nonsynonymous substitution , biology , single nucleotide polymorphism , genetics , disease , phenotype , genome , computational biology , evolutionary biology , bioinformatics , genotype , gene , medicine , pathology

Nonsynonymous single nucleotide polymorphisms (nsSNPs) are prevalent in genomes and are closely associated with inherited diseases. To facilitate identifying disease-associated nsSNPs from a large number of neutral nsSNPs, it is important to develop computational tools to predict the nsSNP's phenotypic effect (disease-associated versus neutral). nsSNPAnalyzer, a web-based software developed for this purpose, extracts structural and evolutionary information from a query nsSNP and uses a machine learning method called Random Forest to predict the nsSNP's phenotypic effect. nsSNPAnalyzer server is available at http://snpanalyzer.utmem.edu/.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research