Associated Papers
A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome.
Fortuno C et al.
Genome Medicine, 2025
41126324 (PubMed )
Supplement: 13073_2025_1536_MOESM1_ESM.xlsx › Table_S1
TP53_PROF: a machine learning model to predict impact of missense mutations in TP53.
Ben-Cohen G et al.
Briefings in Bioinformatics, 2022
35043155 (PubMed )
Supplement: supplementary_table_s1_bbab524.xlsx › S1B._Negative_Set
The dark matter of the cancer genome: aberrations in regulatory elements, untranslated regions, splice sites, non-coding RNA and synonymous mutations.
Diederichs S et al.
Embo Molecular Medicine, 2016
26992833 (PubMed )
Supplement: EMMM-8-442-s002.docx
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