Associated Papers
Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification.
Padigepati SR et al.
Human Genetics, 2024
39085601 (PubMed )
Supplement: 439_2024_2691_MOESM2_ESM.xlsx › TP53
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
Comprehensive Identification of Deleterious TP53 Missense VUS Variants Based on Their Impact on TP53 Structural Stability.
Tam B et al.
International Journal of Molecular Sciences, 2021
Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability.
Reza MN et al.
Scientific Reports, 2021
34584144 (PubMed )
Supplement: 41598_2021_98547_MOESM1_ESM.zip › Supplementary_files-5-8-21 › Supplementary_file_3.xlsx › Sheet1
Identification of relevant genetic alterations in cancer using topological data analysis.
Rabadán R et al.
Nature Communications, 2020
32732999 (PubMed )
Supplement: 41467_2020_17659_MOESM3_ESM.xls › TableS1
Combining Ramachandran plot and molecular dynamics simulation for structural-based variant classification: Using TP53 variants as model.
Tam B et al.
Computational and Structural Biotechnology Journal, 2020
33363700 (PubMed )
Supplement: mmc1.xlsx › Sheet1
Pancreatic Juice Mutation Concentrations Can Help Predict the Grade of Dysplasia in Patients Undergoing Pancreatic Surveillance.
Suenaga M et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research, 2018
Clinical impact of the subclonal architecture and mutational complexity in chronic lymphocytic leukemia.
Nadeu F et al.
Leukemia, 2018
28924241 (PubMed )
Supplement: leu2017291x5.xlsx › Table_S9
Genetic determinants of neuronal vulnerability to apoptosis.
Almeida A
Cellular and Molecular Life Sciences : Cmls, 2013
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