Associated Papers
Precision in prediction: tailoring machine learning models for breast cancer missense variants pathogenicity prediction.
Ahmad RM et al.
Briefings in Bioinformatics, 2025
Mutational landscape of triple-negative breast cancer in African American women.
Yao S et al.
Nature Genetics, 2025
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
Familial history and prevalence of BRCA1, BRCA2 and TP53 pathogenic variants in HBOC Brazilian patients from a public healthcare service.
Matta BP et al.
Scientific Reports, 2022
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
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
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
A Bayesian framework for efficient and accurate variant prediction.
Qian D et al.
Plos One, 2018
Dealing With BRCA1/2 Unclassified Variants in a Cancer Genetics Clinic: Does Cosegregation Analysis Help?
Zuntini R et al.
Frontiers in Genetics, 2018
iFish: predicting the pathogenicity of human nonsynonymous variants using gene-specific/family-specific attributes and classifiers.
Wang M et al.
Scientific Reports, 2016
Germline variation in cancer-susceptibility genes in a healthy, ancestrally diverse cohort: implications for individual genome sequencing.
Bodian DL et al.
Plos One, 2014
BRCA1/2 mutation analysis in 41 ovarian cell lines reveals only one functionally deleterious BRCA1 mutation.
Stordal B et al.
Molecular Oncology, 2013
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
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
BRCA1 and BRCA2 mutation analysis of early-onset and familial breast cancer cases in Mexico.
Ruiz-Flores P et al.
Human Mutation, 2002
[Breast cancer genetics. BRCA1 and BRCA2: the main genes for disease predisposition].
Ruiz-Flores P et al.
Revista De Investigacion Clinica; Organo Del Hospital De Enfermedades De La Nutricion, 0
Clinical follow up of mexican women with early onset of breast cancer and mutations in the BRCA1 and BRCA2 genes.
Calderón-Garcidueñas AL et al.
Salud Publica De Mexico, 0
Screening of Germline BRCA1 and BRCA2 Variants in Nigerian Breast Cancer Patients.
Onyia AF et al.
Technology in Cancer Research & Treatment, 0