Article

ePat: extended PROVEAN annotation tool

2021-12-23

Abstract excerpt

The ‘ePat’ (extended PROVEAN annotation tool) is a software tool that extends the functionality of PROVEAN: a software tool for predicting whether amino acid substitutions and indels will affect the biological function of proteins. The ‘ePat’ extends the conventional PROVEAN to enable the following two things, which the conventional PROVEAN could not calculate the pathogenicity of these variants. First is to calcu...

Topics

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

Identifiers and source

Literature Corpus work: 35ab1d39-7b8a-55da-bab3-cfb4c592ec85
DOI: 10.1101/2021.12.21.468911

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

ePat: extended PROVEAN annotation toolDOI 10.1101/2021.12.21.468911Read

PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels.Semantic proximity Read

REVEL Is Better at Predicting Pathogenicity of Loss-of-Function than Gain-of-Function VariantsSemantic proximity Read

Evaluation of computational techniques for predicting non-synonymous single nucleotide variants pathogenicity.Semantic proximity Read

REVEL is better at predicting pathogenicity of loss-of-function than gain-of-function variantsSemantic proximity Read

An integrative framework for clinical diagnosis and knowledge discovery from exome sequencing data.Semantic proximity Read

Evaluation of<i>in silico</i>pathogenicity prediction tools for the classification of small in-frame indelsSemantic proximity Read

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense VariantsSemantic proximity Read

Refinement of the clinical variant interpretation framework by statistical evidence and machine learning.Semantic proximity Read

Predicting the functional effect of amino acid substitutions and indels.Semantic proximity Read

Annotation of Human Exome Gene Variants with Consensus PathogenicitySemantic proximity Read

3Cnet: Pathogenicity prediction of human variants using knowledge transfer with deep recurrent neural networksSemantic proximity Read

The SAAP pipeline and database: tools to analyze the impact and predict the pathogenicity of mutations.Semantic proximity Read