In silico analysis of missense substitutions using sequence-alignment based methods

BY IN Functional impact prediction, Journal Club, Review NO COMMENTS YET , , , , , , , ,

Computational classifiers classify missense substitutions as pathogenetic or neutral based on inferences from evolutionary conservation using protein multiple sequence alignments (PMSAs) of the gene of interest (and other features). In this review, Tavtigian et al. make suggestions with respect to the important aspects of creating PMSAs that are informative for classification (and more). In using

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Congruency in the prediction of pathogenic missense mutations: state-of-the-art web-based tools

BY IN Functional impact prediction, Journal Club, Review NO COMMENTS YET , , , , , , ,

Deep sequencing initiatives are identified a remarkable quantity of single nucleotide polymorphisms yet only approximately half are nonsynonymous amino acid substitutions that could potentially affect protein function. A confusing array of tools are available to help identify the few gene-coding variants that actually cause or confer susceptibility to disease. In this brief, Castellana and Mazza

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