Sublinear growth of information in DNA sequences.
We introduce a novel method to analyse complete genomes and recognise some distinctive features by means of an adaptive compression algorithm, which is not DNA-oriented, based on the Lempel-Ziv scheme. We study the Information Content as a function of the number of symbols encoded by the algorithm and we analyse the dictionary created by the algorithm. Preliminary results are shown concerning regions showing a sublinear type of information growth, which is strictly connected to the presence of highly repetitive subregions that might be supposed to have a regulatory function within the genome.
Menconi
Giulia
G
Dipartimento di Matematica Applicata, Università di Pisa, Via Bonanno 26/b, 56125 Pisa, Italy. menconi@mail.dm.unipi.it
D000465:Algorithms; D021901:DNA, Intergenic; D005091:Exons; D016678:Genome; D007438:Introns; D008037:Linguistics; D008969:Molecular Sequence Data
D021901:DNA, Intergenic