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Genome-wide analysis of promoters: clustering by alignment and analysis of regular patterns.


ABSTRACT: In this paper we perform a genome-wide analysis of H. sapiens promoters. To this aim, we developed and combined two mathematical methods that allow us to (i) classify promoters into groups characterized by specific global structural features, and (ii) recover, in full generality, any regular sequence in the different classes of promoters. One of the main findings of this analysis is that H. sapiens promoters can be classified into three main groups. Two of them are distinguished by the prevalence of weak or strong nucleotides and are characterized by short compositionally biased sequences, while the most frequent regular sequences in the third group are strongly correlated with transposons. Taking advantage of the generality of these mathematical procedures, we have compared the promoter database of H. sapiens with those of other species. We have found that the above-mentioned features characterize also the evolutionary content appearing in mammalian promoters, at variance with ancestral species in the phylogenetic tree, that exhibit a definitely lower level of differentiation among promoters.

SUBMITTER: Pettinato L 

PROVIDER: S-EPMC3898993 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Genome-wide analysis of promoters: clustering by alignment and analysis of regular patterns.

Pettinato Lucia L   Calistri Elisa E   Di Patti Francesca F   Livi Roberto R   Luccioli Stefano S  

PloS one 20140122 1


In this paper we perform a genome-wide analysis of H. sapiens promoters. To this aim, we developed and combined two mathematical methods that allow us to (i) classify promoters into groups characterized by specific global structural features, and (ii) recover, in full generality, any regular sequence in the different classes of promoters. One of the main findings of this analysis is that H. sapiens promoters can be classified into three main groups. Two of them are distinguished by the prevalenc  ...[more]

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