Associated Papers
TP53 mutation heterogeneity reveals distinct prognoses in mantle cell lymphoma.
Liu S et al.
Annals of Hematology, 2026
41559357 (PubMed )
Supplement: 277_2026_6771_MOESM2_ESM.xlsx › TableS3
Characteristics predicting reduced penetrance variants in the high-risk cancer predisposition gene TP53.
Fortuno C et al.
Hgg Advances, 2025
40696762 (PubMed )
Supplement: mmc2.xlsx › Supplemental_Table_3
TP53 variant clusters stratify phenotypic diversity in germline carriers and reveal an osteosarcoma-prone subgroup.
Fischer NW et al.
Nature Communications, 2025
41022739 (PubMed )
Supplement: 41467_2025_63528_MOESM7_ESM.xlsx › Sheet1
TP53 minigene analysis of 161 sequence changes provides evidence for role of spatial constraint and regulatory elements on variant-induced splicing impact.
Canson DM et al.
Npj Genomic Medicine, 2025
40341019 (PubMed )
Supplement: 41525_2025_498_MOESM2_ESM.xlsx › Data_S2
Deep CRISPR mutagenesis characterizes the functional diversity of TP53 mutations.
Funk JS et al.
Nature Genetics, 2025
39774325 (PubMed )
Supplement: 41588_2024_2039_MOESM5_ESM.xlsx › SuppFig6
Genomic Features of Newly Diagnosed Large B-cell Lymphoma with or without Subsequent Disease Progression.
Landsburg DJ et al.
Cancer Research Communications, 2024
39392347 (PubMed )
Supplement: crc-24-0337_supplementary_data_suppsd.xlsx › Supplemental_Table_1
Comprehensive classification of TP53 somatic missense variants based on their impact on p53 structural stability.
Tam B et al.
Briefings in Bioinformatics, 2024
39140857 (PubMed )
Supplement: table_s1_bbae400.xlsx › Sheet1
Genomic Profiling of Primary Diffuse Large B-Cell Lymphoma of the Central Nervous System Suggests Novel Potential Therapeutic Targets.
Agostinelli C et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc, 2023
Integration of deep learning with Ramachandran plot molecular dynamics simulation for genetic variant classification.
Tam B et al.
Iscience, 2023
36879825 (PubMed )
Supplement: mmc2.xlsx › MSH2
Finding driver mutations in cancer: Elucidating the role of background mutational processes.
Brown AL et al.
Plos Computational Biology, 2019
31034466 (PubMed )
Supplement: pcbi.1006981.s010.xlsx › final_benchmark
Germ-line and somatic EPHA2 coding variants in lens aging and cataract.
Bennett TM et al.
Plos One, 2017
29267365 (PubMed )
Supplement: pone.0189881.s007.xlsx › S7a._Clear__1__all
Epidemiology of doublet/multiplet mutations in lung cancers: evidence that a subset arises by chronocoordinate events.
Chen Z et al.
Plos One, 2008
19005564 (PubMed )
Supplement: pone.0003714.s007.xls › Table_s-5
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