Associated Papers
Precision in prediction: tailoring machine learning models for breast cancer missense variants pathogenicity prediction.
Ahmad RM et al.
Briefings in Bioinformatics, 2025
Functional evaluation and clinical classification of BRCA2 variants.
Huang H et al.
Nature, 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
Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer.
Keskin Karakoyun H et al.
Frontiers in Genetics, 2023
Classification of BRCA2 Variants of Uncertain Significance (VUS) Using an ACMG/AMP Model Incorporating a Homology-Directed Repair (HDR) Functional Assay.
Hu C et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research, 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
Breast cancer risks associated with missense variants in breast cancer susceptibility genes.
Dorling L et al.
Genome Medicine, 2022
Variomes: a high recall search engine to support the curation of genomic variants.
Pasche E et al.
Bioinformatics (oxford, England), 2022
Identification of pathogenic variants in cancer genes using base editing screens with editing efficiency correction.
Huang C et al.
Genome Biology, 2021
Strong functional data for pathogenicity or neutrality classify BRCA2 DNA-binding-domain variants of uncertain significance.
Richardson ME et al.
American Journal of Human Genetics, 2021
Olaparib is effective for recurrent urothelial carcinoma with BRCA2 pathogenic germline mutation: first report on olaparib response in recurrent UC.
Yang H et al.
Therapeutic Advances in Medical Oncology, 2020
REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification.
Tian Y et al.
Scientific Reports, 2019
Toward automation of germline variant curation in clinical cancer genetics.
Ravichandran V et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 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
Assessment of the Clinical Relevance of BRCA2 Missense Variants by Functional and Computational Approaches.
Guidugli L et al.
American Journal of Human Genetics, 2018
A Bayesian framework for efficient and accurate variant prediction.
Qian D et al.
Plos One, 2018
Biological and clinical evidence for somatic mutations in BRCA1 and BRCA2 as predictive markers for olaparib response in high-grade serous ovarian cancers in the maintenance setting.
Dougherty BA et al.
Oncotarget, 2017
Classifying Variants of Undetermined Significance in BRCA2 with protein likelihood ratios.
Karchin R et al.
Cancer Informatics, 2008