title: MUT-TP53 2.0: a novel versatile matrix for statistical analysis of TP53 mutations in human cancer.
abstract: Analysis of the literature reporting p53 mutations shows that 8% of report display typographical mistakes with a notable increase in recent years. These errors are sometimes isolated, but in some cases, they concern several or even all mutations described in a single article. Furthermore, some works report unusual profile of p53 mutations whose accuracy is difficult to assess. To handle these problems we have developed MUT-TP53 2.0, an accurate and powerful tool that will automatically handle p53 mutations and generate tables ready for publication that will lower the risk of typographical errors. Furthermore, using functional and statistical information issued from the UMD p53 database, it allows to assess the biological activity and the likelihood of every p53 mutant.
authors.affiliation: Karolinska Institute Department of Oncology-Pathology Cancer Center Karolinska, Stockholm, Sweden. thierry.soussi@ki.se
authors.forename: Thierry
authors.initials: T
authors.lastname: Soussi
authors.forename: Dalil
authors.initials: D
authors.lastname: Hamroun
authors.forename: Linn
authors.initials: L
authors.lastname: Hjortsberg
authors.forename: Jean Michel
authors.initials: JM
authors.lastname: Rubio-Nevado
authors.forename: Jean Louis
authors.initials: JL
authors.lastname: Fournier
authors.forename: Christophe
authors.initials: C
authors.lastname: Béroud
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D006801:Humans; D015201:Meta-Analysis as Topic; D050505:Mutant Proteins / Q000235:genetics; D009154:Mutation / Q000235:genetics*; D009369:Neoplasms / Q000235:genetics*; D012984:Software; D013223:Statistics as Topic; D016159:Tumor Suppressor Protein p53 / Q000235:genetics*
chemical_list: D050505:Mutant Proteins; D016159:Tumor Suppressor Protein p53