Associated Papers
Integrating evidence from protein domains to identify cancer driver mutations.
Ostroverkhova D et al.
Protein Science : a Publication of the Protein Society, 2026
The Causal Pivot: A structural approach to genetic heterogeneity and variant discovery in complex diseases.
Shaw CA et al.
American Journal of Human Genetics, 2025
VarMeter2: An enhanced structure-based method for predicting pathogenic missense variants through Mahalanobis distance.
Ohno S et al.
Computational and Structural Biotechnology Journal, 2025
SpliceAI-10k calculator for the prediction of pseudoexonization, intron retention, and exon deletion.
Canson DM et al.
Bioinformatics (oxford, England), 2023
APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP.
Walker LC et al.
Medrxiv : the Preprint Server for Health Sciences, 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
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
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
Systematic misclassification of missense variants in BRCA1 and BRCA2 "coldspots".
Dines JN et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2020
REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification.
Tian Y et al.
Scientific Reports, 2019
A plugin for the Ensembl Variant Effect Predictor that uses MaxEntScan to predict variant spliceogenicity.
Shamsani J et al.
Bioinformatics (oxford, England), 2019
Finding driver mutations in cancer: Elucidating the role of background mutational processes.
Brown AL et al.
Plos Computational Biology, 2019
Clinically Actionable Insights into Initial and Matched Recurrent Glioblastomas to Inform Novel Treatment Approaches.
Ellis HP et al.
Journal of Oncology, 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
Longitudinal analysis of treatment-induced genomic alterations in gliomas.
Erson-Omay EZ et al.
Genome Medicine, 2017
Clinical Next-Generation Sequencing Pipeline Outperforms a Combined Approach Using Sanger Sequencing and Multiplex Ligation-Dependent Probe Amplification in Targeted Gene Panel Analysis.
Schenkel LC et al.
The Journal of Molecular Diagnostics : Jmd, 2016
New recurrent BRCA1/2 mutations in Polish patients with familial breast/ovarian cancer detected by next generation sequencing.
Kluska A et al.
Bmc Medical Genomics, 2015
Benchmarking mutation effect prediction algorithms using functionally validated cancer-related missense mutations.
Martelotto LG et al.
Genome Biology, 2014
Rapid evolution of BRCA1 and BRCA2 in humans and other primates.
Lou DI et al.
Bmc Evolutionary Biology, 2014
A guide for functional analysis of BRCA1 variants of uncertain significance.
Millot GA et al.
Human Mutation, 2012
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 one-step prescreening for point mutations and large rearrangement in BRCA1 and BRCA2 genes using quantitative polymerase chain reaction and high-resolution melting curve analysis.
Coulet F et al.
Genetic Testing and Molecular Biomarkers, 2010
Characterization of BRCA1 and BRCA2 deleterious mutations and variants of unknown clinical significance in unilateral and bilateral breast cancer: the WECARE study.
Borg A et al.
Human Mutation, 2010
Impact of BRCA1 and BRCA2 variants on splicing: clues from an allelic imbalance study.
Caux-Moncoutier V et al.
European Journal of Human Genetics : Ejhg, 2009
Evaluation of unclassified variants in the breast cancer susceptibility genes BRCA1 and BRCA2 using five methods: results from a population-based study of young breast cancer patients.
Lee E et al.
Breast Cancer Research : Bcr, 2008
Racial differences in the incidence of BRCA1 and BRCA2 mutations in a cohort of early onset breast cancer patients: African American compared to white women.
Haffty BG et al.
Journal of Medical Genetics, 2006
Application of embryonic lethal or other obvious phenotypes to characterize the clinical significance of genetic variants found in trans with known deleterious mutations.
Judkins T et al.
Cancer Research, 2005
Truncating BRCA1 mutations are uncommon in a cohort of hereditary prostate cancer families with evidence of linkage to 17q markers.
Zuhlke KA et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research, 2004
Analysis of missense variation in human BRCA1 in the context of interspecific sequence variation.
Abkevich V et al.
Journal of Medical Genetics, 2004