Associated Papers
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
Targeted sequencing of FH-deficient uterine leiomyomas reveals biallelic inactivating somatic fumarase variants and allows characterization of missense variants.
Popp B et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc, 2020
32612247 (PubMed )
Supplement: 41379_2020_596_MOESM2_ESM.xlsx › allFH_missense
From uncertainty to pathogenicity: clinical and functional interrogation of a rare TP53 in-frame deletion.
Quinn EA et al.
Cold Spring Harbor Molecular Case Studies, 2019
30886117 (PubMed )
Supplement: supp_mcs.a003921_Supplemental_Table_1a.xlsx › S_Table1a._TP53_in_ClinVar
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