Associated Papers
Precision in prediction: tailoring machine learning models for breast cancer missense variants pathogenicity prediction.
Ahmad RM et al.
Briefings in Bioinformatics, 2025
Decoding the molecular landscape: HER2 and PD-L1 in advanced gastric cancer.
Yao J et al.
Frontiers in Immunology, 2025
Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer.
Keskin Karakoyun H et al.
Frontiers in Genetics, 2023
Clinical, splicing, and functional analysis to classify BRCA2 exon 3 variants: Application of a points-based ACMG/AMP approach.
Thomassen M et al.
Human Mutation, 2022
A Comprehensive Evaluation of the Performance of Prediction Algorithms on Clinically Relevant Missense Variants.
Qorri E et al.
International Journal of Molecular Sciences, 2022
An integrative model for the comprehensive classification of BRCA1 and BRCA2 variants of uncertain clinical significance.
Iversen ES et al.
Npj Genomic Medicine, 2022
Variomes: a high recall search engine to support the curation of genomic variants.
Pasche E et al.
Bioinformatics (oxford, England), 2022
Cancer-causing BRCA2 missense mutations disrupt an intracellular protein assembly mechanism to disable genome maintenance.
Lee M et al.
Nucleic Acids Research, 2021
REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification.
Tian Y et al.
Scientific Reports, 2019
Germline variation in BRCA1/2 is highly ethnic-specific: Evidence from over 30,000 Chinese hereditary breast and ovarian cancer patients.
Bhaskaran SP et al.
International Journal of Cancer, 2019
Comprehensive annotation of BRCA1 and BRCA2 missense variants by functionally validated sequence-based computational prediction models.
Hart SN et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2019
Minigene Splicing Assays Identify 12 Spliceogenic Variants of BRCA2 Exons 14 and 15.
Fraile-Bethencourt E et al.
Frontiers in Genetics, 2019
Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics.
Ernst C et al.
Bmc Medical Genomics, 2018
A Bayesian framework for efficient and accurate variant prediction.
Qian D et al.
Plos One, 2018
DNA repair-related functional assays for the classification of BRCA1 and BRCA2 variants: a critical review and needs assessment.
Toland AE et al.
Journal of Medical Genetics, 2017
Functional assays for analysis of variants of uncertain significance in BRCA2.
Guidugli L et al.
Human Mutation, 2014
A review of a multifactorial probability-based model for classification of BRCA1 and BRCA2 variants of uncertain significance (VUS).
Lindor NM et al.
Human Mutation, 2012
A high-throughput protocol for mutation scanning of the BRCA1 and BRCA2 genes.
Hondow HL et al.
Bmc Cancer, 2011