SNAP predicts effect of mutations on protein function

Abstract

Many non-synonymous single nucleotide polymorphisms (nsSNPs) in humans are suspected to impact protein function. Here, we present a publicly available server implementation of the method SNAP (screening for non-acceptable polymorphisms) that predicts the functional effects of single amino acid substitutions. SNAP identifies over 80% of the non-neutral mutations at 77% accuracy and over 76% of the neutral mutations at 80% accuracy at its default threshold. Each prediction is associated with a reliability index that correlates with accuracy and thereby enables experimentalists to zoom into the most promising predictions.

Publication
Bioinformatics
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Yana Bromberg
Principal Investigator - Associate Professor of Bioinformatics

My research focuses on deciphering the DNA blueprints of life’s molecular machinery