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
Uncovering the Contribution of Moderate-Penetrance Susceptibility Genes to Breast Cancer by Whole-Exome Sequencing and Targeted Enrichment Sequencing of Candidate Genes in Women of European Ancestry.
Dumont M et al.
Cancers, 2022
35884425 (PubMed )
Supplement: cancers-14-03363-s001.zip › Table_S11-final_16052022.xlsx › Table_S11B
Assessing the clinical value of targeted massively parallel sequencing in a longitudinal, prospective population-based study of cancer patients.
Wong SQ et al.
British Journal of Cancer, 2015
25742471 (PubMed )
Supplement: bjc201580x7.xls › Supp_Table_3
NGS-based profiling of key cancer genes in Indian triple-negative breast cancer patients reinforces molecular heterogeneity of the disease.
Sahasrabuddhe NA et al.
Indian Journal of Cancer, 0
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