Article

E-SNPs&GO: Embedding of protein sequence and function improves the annotation of human pathogenic variants

2022-05-11

Abstract excerpt

<h4>Motivation</h4> The advent of massive DNA sequencing technologies is producing a huge number of human single-nucleotide polymorphisms occurring in protein-coding regions and possibly changing protein sequences. Discriminating harmful protein variations from neutral ones is one of the crucial challenges in precision medicine. Computational tools based on artificial intelligence provide models for protein seque...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 9b04ade7-8b02-50bc-a71f-4cdb11a84b58
DOI: 10.1101/2022.05.10.491314

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

E-SNPs&GO: Embedding of protein sequence and function improves the annotation of human pathogenic variantsDOI 10.1101/2022.05.10.491314Read

E-SNPs&GO: embedding of protein sequence and function improves the annotation of human pathogenic variants.Semantic proximity Read

Functional annotations improve the predictive score of human disease-related mutations in proteins.Semantic proximity Read

Genome-wide prediction of disease variants with a deep protein language modelSemantic proximity Read

VUS. Life: Leveraging Vector Embeddings for Rapid and Accurate Pathogenicity Prediction of Genetic VariantsSemantic proximity Read

Semantic embedding of variant effect annotations enables rapid and accurate pathogenicity prediction with VUS.Life.Semantic proximity Read

Utilizing protein structure graph embeddings to predict the pathogenicity of missense variantsSemantic proximity Read

PATHOS: Predicting Variant Pathogenicity by Combining Protein Language Models and Biological FeaturesSemantic proximity Read

Learning sequence to predict gain- or loss-of-function variantsSemantic proximity Read

Protein Language Model Predicts Mutation Pathogenicity and Clinical PrognosisSemantic proximity Read

Protein Language Models Rescue Variant Pathogenicity Prediction in Intrinsically Disordered Regions Through Synergistic Integration with Structure-Based MethodsSemantic proximity Read

WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation.Semantic proximity Read

An augmented transformer model trained on family specific variant data leads to improved prediction of variants of uncertain significanceSemantic proximity Read