Associated Papers
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
SPiP: Splicing Prediction Pipeline, a machine learning tool for massive detection of exonic and intronic variant effects on mRNA splicing.
Leman R et al.
Human Mutation, 2022
Enrichment of "Cribriform" morphologies (intraductal and cribriform adenocarcinoma) and genomic alterations in radiorecurrent prostate cancer.
Shah RB et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc, 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
Understanding and predicting the functional consequences of missense mutations in BRCA1 and BRCA2.
Aljarf R et al.
Scientific Reports, 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
Comparison of in silico strategies to prioritize rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders.
Rowlands C et al.
Scientific Reports, 2021
Cancer-causing BRCA2 missense mutations disrupt an intracellular protein assembly mechanism to disable genome maintenance.
Lee M et al.
Nucleic Acids Research, 2021
Calibration of Pathogenicity Due to Variant-Induced Leaky Splicing Defects by Using BRCA2 Exon 3 as a Model System.
Tubeuf H et al.
Cancer Research, 2020
Blood RNA analysis can increase clinical diagnostic rate and resolve variants of uncertain significance.
Wai HA et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2020
Consolidated BRCA1/2 Variant Interpretation by MH BRCA Correlates with Predicted PARP Inhibitor Efficacy Association by MH Guide.
Hirotsu Y et al.
International Journal of Molecular Sciences, 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
Insights into BRCA Cancer Predisposition from Integrated Germline and Somatic Analyses in 7632 Cancers.
Yost S et al.
Jnci Cancer Spectrum, 2019
Finding driver mutations in cancer: Elucidating the role of background mutational processes.
Brown AL et al.
Plos Computational Biology, 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
Germline mutations in candidate predisposition genes in individuals with cutaneous melanoma and at least two independent additional primary cancers.
Pritchard AL et al.
Plos One, 2018
A Bayesian framework for efficient and accurate variant prediction.
Qian D et al.
Plos One, 2018
Benchmarking mutation effect prediction algorithms using functionally validated cancer-related missense mutations.
Martelotto LG et al.
Genome Biology, 2014
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
BRCA2 is a moderate penetrance gene contributing to young-onset prostate cancer: implications for genetic testing in prostate cancer patients.
Kote-Jarai Z et al.
British Journal of Cancer, 2011