KvSNP: accurately predicting the effect of genetic variants in voltage-gated potassium channels | Zendy

Lucy F. Stead | Zendy; Ian Wood | Zendy; David R. Westhead | Zendy

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KvSNP: accurately predicting the effect of genetic variants in voltage-gated potassium channels

Author(s) -

Lucy F. Stead,

Ian Wood,

David R. Westhead

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr365

Subject(s) - single nucleotide polymorphism , matthews correlation coefficient , voltage gated potassium channel , receiver operating characteristic , potassium channel , genetic association , correlation , computational biology , disease , genetics , gene , computer science , biology , artificial intelligence , medicine , machine learning , genotype , mathematics , geometry , support vector machine

Non-synonymous single nucleotide polymorphisms (nsSNPs) in voltage-gated potassium (Kv) channels cause diseases with potentially fatal consequences in seemingly healthy individuals. Identifying disease-causing genetic variation will aid presymptomatic diagnosis and treatment of such disorders. NsSNP-effect predictors are hypothesized to perform best when developed for specific gene families. We, thus, created KvSNP: a method that assigns a disease-causing probability to Kv-channel nsSNPs.

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