Bayesian classification for promoter prediction in human DNA sequences

Many Computational methods are yet available for data retrieval and analysis of genomic sequences, but some functional sites are difficult to characterize. In this work, we examine the problem of promoter localization in human DNA sequences. Promoters are regulatory regions that governs the expression of genes, and their prediction is reputed difficult, so that this issue is still open. We present the Chaos Game representation (CGR) of DNA sequences which has many interesting properties, and the notion of ‘genomic signature’ that proved relevant in phylogeny applications. Based on this notion, we develop a (naïve) bayesian classifier, evaluate its performances, and show that its adaptive implementation enable to reveal or assess core-promoter positions along a DNA sequence.