Associated Papers
MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model.
Karalidou V et al.
Biomolecules, 2022
36358902 (PubMed )
Supplement: biomolecules-12-01552-s001.zip › final_annotation_file_CanVaS.xlsx › Sheet1
Analysis of single-nucleotide polymorphisms in genes associated with triple-negative breast cancer.
G V et al.
Frontiers in Genetics, 2022
36561320 (PubMed )
Supplement: Table2.xlsx › TP53
Next-generation sequencing unravels extensive genetic alteration in recurrent ovarian cancer and unique genetic changes in drug-resistant recurrent ovarian cancer.
Du ZH et al.
Molecular Genetics & Genomic Medicine, 2018
Dealing With BRCA1/2 Unclassified Variants in a Cancer Genetics Clinic: Does Cosegregation Analysis Help?
Zuntini R et al.
Frontiers in Genetics, 2018
Multi-platform molecular profiling of a large cohort of glioblastomas reveals potential therapeutic strategies.
Xiu J et al.
Oncotarget, 2016
26933808 (PubMed )
Supplement: oncotarget-07-21556-s001.pdf
High prevalence of BRCA1 founder mutations in Greek breast/ovarian families.
Konstantopoulou I et al.
Clinical Genetics, 2014
High incidence of protein-truncating TP53 mutations in BRCA1-related breast cancer.
Holstege H et al.
Cancer Research, 2009
Harmonized microarray/mutation scanning analysis of TP53 mutations in undissected colorectal tumors.
Favis R et al.
Human Mutation, 2004
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