Associated Papers
Phenotypic evaluation of deep learning models for classifying germline variant pathogenicity.
Chow RD et al.
Npj Precision Oncology, 2024
39427061 (PubMed )
Supplement: 41698_2024_710_MOESM2_ESM.xlsx › S3
The Potential of Genetics in Identifying Women at Lower Risk of Breast Cancer.
Bolze A et al.
Jama Oncology, 2024
38153744 (PubMed )
Supplement: jamaoncol-e235468-s002.xlsx › eTable_4
Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability.
Reza MN et al.
Scientific Reports, 2021
34584144 (PubMed )
Supplement: 41598_2021_98547_MOESM1_ESM.zip › Supplementary_files-5-8-21 › Supplementary_file_2.xlsx › Sheet1
Analysis of Sequence and Copy Number Variants in Canadian Patient Cohort With Familial Cancer Syndromes Using a Unique Next Generation Sequencing Based Approach.
Bhai P et al.
Frontiers in Genetics, 2021
34326862 (PubMed )
Supplement: Data_Sheet_1.zip › Supplementary_files › Supplementary_Table_S4.xlsx › Every_test
Germline Pathogenic Variants in 7636 Japanese Patients With Prostate Cancer and 12 366 Controls.
Momozawa Y et al.
Journal of the National Cancer Institute, 2020
31214711 (PubMed )
Supplement: djz124_supplementary_data.zip › djz124-Suppl_Data › Supplementary_Tables_5_and_6_060619.xlsx › Supplementary_Table_6
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