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.