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High risk nsSNPs identified by five <i>in silico</i> programs.

NIAID Data Ecosystem2026-03-10 收录

变异致病性预测

nsSNP风险筛选

数据链接：

https://figshare.com/articles/dataset/High_risk_nsSNPs_identified_by_five_i_in_silico_i_programs_/5784117 数据链接链接失效反馈

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资源简介：

High risk nsSNPs identified by five in silico programs.

应用场景：

创建时间：

2018-01-13

变异致病性预测

外显子组关联分析

CAPICE is a computational method for predicting the pathogenicity of SNVs and InDels. Repository description: 1) "paper_datasets.tar.gz" contains all datasets used in the CAPICE paper; 2) "CAPIC

NIAID Data Ecosystem110

Additional file 3 of Comprehensive analysis of germline mutations in northern Brazil: a panel of 16 genes for hereditary cancer-predisposing syndrome investigation

癌症遗传易感性

变异致病性预测

Additional file 3: Supplementary Table S3 Pathogenicity prediction of the variants of uncertain significance.

NIAID Data Ecosystem80

Additional file 2 of Conserved missense variant pathogenicity and correlated phenotypes across paralogous genes

变异致病性预测

临床遗传学分析

Additional file 2. Table S1: List of amino acid residues overlapping with paralogous (likely)-pathogenic variants from ClinVar ≥ 1 review star.

Figshare2025-07-07 更新70

GEMVAP Training Data

变异致病性预测

生物学建模

This dataset has been used to train a gene-specific pathogenicity predictor model called GEMVAP.

DataCite Commons2025-06-28 更新90

hTRPM4 VUS variants with high ClinPred and paralogue annotation scores.

变异致病性预测

TRPM4基因功能

hTRPM4 VUS variants with high ClinPred and paralogue annotation scores.

NIAID Data Ecosystem80

High risk nsSNPs identified by five <i>in silico</i> programs.

资源简介：

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