Varaico: Literature-Extracted Genetic Variants

Gene:MSH2
Variant:p.E198G
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MSH2

NM_000251.3:p.E198G

Associated Papers

VarMeter2: An enhanced structure-based method for predicting pathogenic missense variants through Mahalanobis distance.

Ohno S et al.

Computational and Structural Biotechnology Journal, 2025

40160862 (PubMed )
Supplement: mmc2.xlsx › Sheet1

Next-generation sequencing uncovers crucial mutated genes and potential therapeutic targets in ovarian cancer patients.

Zhao T et al.

American Journal of Translational Research, 2024

SpliceAI-10k calculator for the prediction of pseudoexonization, intron retention, and exon deletion.

Canson DM et al.

Bioinformatics (oxford, England), 2023

37021934 (PubMed )
Supplement: btad179_supplementary_data.zip › SAI10kcalc_supp_tables_final.xlsx › S1.variants

Integration of deep learning with Ramachandran plot molecular dynamics simulation for genetic variant classification.

Tam B et al.

Iscience, 2023

36879825 (PubMed )
Supplement: mmc2.xlsx › MSH2

Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer.

Keskin Karakoyun H et al.

Frontiers in Genetics, 2023

36896237 (PubMed )
Supplement: Table1.xlsx › clinvar_breastcancer_allvariant

Protein domains provide a new layer of information for classifying human variations in rare diseases.

Corcuff M et al.

Frontiers in Bioinformatics, 2023

36896423 (PubMed )
Supplement: Table1.XLSX › Supplementary_Table_1

Identification of SNPs in hMSH3/MSH6 interaction domain affecting the structure and function of MSH2 protein.

Singh S et al.

Biotechnology and Applied Biochemistry, 2022

Quantifying prediction of pathogenicity for within-codon concordance (PM5) using 7541 functional classifications of BRCA1 and MSH2 missense variants.

Loong L et al.

Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2022

34906453 (PubMed )
Supplement: mmc1.xlsx › Sup_Table2_Assay_ClinVar

Disease variant prediction with deep generative models of evolutionary data.

Frazer J et al.

Nature, 2021

The Frequency of Discordant Variant Classification in the Human Gene Mutation Database: A Comparison of the American College of Medical Genetics and Genomics Guidelines and ClinVar.

Park KJ et al.

Laboratory Medicine, 2021

Massively parallel functional testing of MSH2 missense variants conferring Lynch syndrome risk.

Jia X et al.

American Journal of Human Genetics, 2021

Contribution of mRNA Splicing to Mismatch Repair Gene Sequence Variant Interpretation.

Thompson BA et al.

Frontiers in Genetics, 2020

32849802 (PubMed )
Supplement: Data_Sheet_1.xlsx › Supplementary_Table_3

Novel Genetic Markers for Early Detection of Elevated Breast Cancer Risk in Women.

Wu B et al.

International Journal of Molecular Sciences, 2019

Methylation Tolerance-Based Functional Assay to Assess Variants of Unknown Significance in the MLH1 and MSH2 Genes and Identify Patients With Lynch Syndrome.

Bouvet D et al.

Gastroenterology, 2019

A plugin for the Ensembl Variant Effect Predictor that uses MaxEntScan to predict variant spliceogenicity.

Shamsani J et al.

Bioinformatics (oxford, England), 2019

30475984 (PubMed )
Supplement: bty960_supplementary_data.zip › bty960-Suppl_data › Supplementary_Table_S1.xlsx › Sheet1

A Bayesian framework for efficient and accurate variant prediction.

Qian D et al.

Plos One, 2018

30212499 (PubMed )
Supplement: pone.0203553.s008.xlsx › Variants

Evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines.

Ghosh R et al.

Genome Biology, 2017

Evaluation of CADD Scores in Curated Mismatch Repair Gene Variants Yields a Model for Clinical Validation and Prioritization.

van der Velde KJ et al.

Human Mutation, 2015

25871441 (PubMed )
Supplement: HUMU-36-712-s001.pdf

Functional analysis of human mismatch repair gene mutations identifies weak alleles and polymorphisms capable of polygenic interactions.

Martinez SL et al.

Proceedings of the National Academy of Sciences of the United States of America, 2010

The first functional study of MLH3 mutations found in cancer patients.

Korhonen MK et al.

Genes, Chromosomes & Cancer, 2008

Functional characterization of pathogenic human MSH2 missense mutations in Saccharomyces cerevisiae.

Gammie AE et al.

Genetics, 2007

Characterization of pathogenic human MSH2 missense mutations using yeast as a model system: a laboratory course in molecular biology.

Gammie AE et al.

Cell Biology Education, 2004

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