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
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
Feasibility of a workflow for the molecular characterization of single cells by next generation sequencing.
Salvianti F et al.
Biomolecular Detection and Quantification, 2015
Assessment of computational methods for predicting the effects of missense mutations in human cancers.
Gnad F et al.
Bmc Genomics, 2013
23819521 (PubMed )
Supplement: 1471-2164-14-S3-S7-S1.xlsx › COSMIC
Cancer-associated p53 tetramerization domain mutants: quantitative analysis reveals a low threshold for tumor suppressor inactivation.
Kamada R et al.
The Journal of Biological Chemistry, 2011
Effects of tumor-associated mutations in the p53 tetramerization domain on oligomerization state and transcriptional activity.
Kamada R et al.
Advances in Experimental Medicine and Biology, 2009
Select a paper to view details