A comprehensive approach for validating p53 binding site predictions

Predicting the locations of Response Elements (RE) has received considerable attention in the field of gene sequence analysis and bioinformatics. Protein53 (p53) has a prominent role in the cell cycle and cancer prevention; it functions as a transcription factor and binds with p53 REs in the DNA. The identification of p53 response elements enlightens the unknown functions and characteristics of p53 besides the genes containing binding sites. In this work, we have proposed an algorithm for validating the prediction of the possible p53 binding sites in the human genome, by incorporating the recent findings on the p53 REs into our suggested profile hidden Markov model (PHMM). We constructed two PHMMs and the results described in this paper are very promising. In the experiments, we have used the p53 REs data reported by Riley et al. [21].