Robert Fragoza

TL;DR: In this article, the authors used patterns of polymorphisms in functionally annotated regions in 1092 humans to identify deleterious variants; then, they experimentally validated candidates, finding regions particularly sensitive to mutations and variants that are disruptive because of mechanistic effects on transcription-factor binding.

TL;DR: It is shown that mutations of predicted and known interface residues disrupt interactions at a similar rate and much more frequently than mutations outside of predicted interfaces.

TL;DR: FissionNet as discussed by the authors is a proteome-wide binary protein interactome for S. pombe, comprising 2,278 high-quality interactions, of which ∼ 50% were previously not reported in any species.

TL;DR: An experimentally and computationally integrated approach to investigate the functional impact of missense mutations in the context of the human interactome network and demonstrate that this interactome perturbation approach offers a generalizable framework for identifying and prioritizingmissense mutations that contribute to the risk of human disease.

TL;DR: SAAMBE-3D is an accurate and fast software applicable for genome-wide studies to assess the effect of amino acid mutations on protein–protein interactions and outperforms currently existing algorithms on various blind-tests.