Associated Papers
Precision in prediction: tailoring machine learning models for breast cancer missense variants pathogenicity prediction.
Ahmad RM et al.
Briefings in Bioinformatics, 2025
41263939 (PubMed )
Supplement: supplementary_materials_bbaf611_1_.zip › Supplementary_materials_bbaf611 › Supplementary_Table_S8.xlsx › Sheet1
The pathogenic role of the BRCA2 c.7847C>T (p.Ser2616Phe) variant in breast and ovarian cancer predisposition.
Yamazawa K et al.
Cancer Science, 2023
37067535 (PubMed )
Supplement: CAS-114-2993-s001.pdf
High-throughput functional evaluation of BRCA2 variants of unknown significance.
Ikegami M et al.
Nature Communications, 2020
32444794 (PubMed )
Supplement: 41467_2020_16141_MOESM4_ESM.xlsx › Information_of_107_variants
Classification of variants of uncertain significance in BRCA1 and BRCA2 using personal and family history of cancer from individuals in a large hereditary cancer multigene panel testing cohort.
Li H et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2020
31853058 (PubMed )
Supplement: 41436_2019_729_MOESM3_ESM.xls › Sheet1
REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification.
Tian Y et al.
Scientific Reports, 2019
31484976 (PubMed )
Supplement: 41598_2019_49224_MOESM2_ESM.xlsx › Sheet1
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
30702160 (PubMed )
Supplement: IJC-145-962-s006.xlsx › Total_BRCA1___BRCA2
A Bayesian framework for efficient and accurate variant prediction.
Qian D et al.
Plos One, 2018
30212499 (PubMed )
Supplement: pone.0203553.s008.xlsx › Variants
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