Associated Papers
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_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
Analysis and Interpretation of the Impact of Missense Variants in Cancer.
Petrosino M et al.
International Journal of Molecular Sciences, 2021
34063805 (PubMed )
Supplement: ijms-22-05416-s001.zip › new_supplementary_file1.xlsx › new_supplementary_file1
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
Disruption of an intermonomer salt bridge in the p53 tetramerization domain results in an increased propensity to form amyloid fibrils.
Galea C et al.
Protein Science : a Publication of the Protein Society, 2005
The relationship among p53 oligomer formation, structure and transcriptional activity using a comprehensive missense mutation library.
Kawaguchi T et al.
Oncogene, 2005
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