Associated Papers
Precision in prediction: tailoring machine learning models for breast cancer missense variants pathogenicity prediction.
Ahmad RM et al.
Briefings in Bioinformatics, 2025
A study of somatic BRCA variants and their putative effect on protein properties in malignant mesothelioma.
Krishnamurthy K et al.
Pleura and Peritoneum, 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
Variomes: a high recall search engine to support the curation of genomic variants.
Pasche E et al.
Bioinformatics (oxford, England), 2022
Whole-Exome Sequencing of Germline Variants in Non-BRCA Families with Hereditary Breast Cancer.
Liu Y et al.
Biomedicines, 2022
Analysis of single-nucleotide polymorphisms in genes associated with triple-negative breast cancer.
G V et al.
Frontiers in Genetics, 2022
Pathogenic nsSNPs that increase the risks of cancers among the Orang Asli and Malays.
Khoruddin NA 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
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
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
Population and breast cancer patients' analysis reveals the diversity of genomic variation of the BRCA genes in the Mexican population.
Fernández-Lopez JC et al.
Human Genomics, 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
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
Mutational analysis of BRCA1 and BRCA2 in hereditary breast and ovarian cancer families from Asturias (Northern Spain).
Blay P et al.
Bmc Cancer, 2013
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 DGGE system for comprehensive mutation screening of BRCA1 and BRCA2: application in a Dutch cancer clinic setting.
van der Hout AH et al.
Human Mutation, 2006