Associated Papers
Genetic landscape of Pakistani familial breast cancer patients using multigene panel testing.
Rashid MU et al.
International Journal of Cancer, 2025
Precision in prediction: tailoring machine learning models for breast cancer missense variants pathogenicity prediction.
Ahmad RM et al.
Briefings in Bioinformatics, 2025
ACMG/AMP interpretation of BRCA1 missense variants: Structure-informed scores add evidence strength granularity to the PP3/BP4 computational evidence.
Ramadane-Morchadi L et al.
American Journal of Human Genetics, 2025
Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification.
Padigepati SR et al.
Human Genetics, 2024
Using Portuguese BRCA pathogenic variation as a model to study the impact of human admixture on human health.
Andaluz S et al.
Bmc Genomics, 2024
DNA repair function scores for 2172 variants in the BRCA1 amino-terminus.
Diabate M et al.
Plos Genetics, 2023
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
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
Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability.
Reza MN et al.
Scientific Reports, 2021
Towards a New, Endophenotype-Based Strategy for Pathogenicity Prediction in BRCA1 and BRCA2: In Silico Modeling of the Outcome of HDR/SGE Assays for Missense Variants.
Özkan S et al.
International Journal of Molecular Sciences, 2021
Classification of variants of uncertain significance in BRCA1 and BRCA2 using personal and family history of cancer from individuals in a large hereditary cancer multigene panel testing cohort.
Li H et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2020
Tumor Testing for Somatic and Germline BRCA1/BRCA2 Variants in Ovarian Cancer Patients in the Context of Strong Founder Effects.
Peixoto A et al.
Frontiers in Oncology, 2020
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
Accurate classification of BRCA1 variants with saturation genome editing.
Findlay GM et al.
Nature, 2018
A Bayesian framework for efficient and accurate variant prediction.
Qian D et al.
Plos One, 2018