Evoliucinis neinformatyvių genetinių sekų modelis

Abstract

The research object is probabilistic properties of non-coding DNA (nucleotide) sequences. Available models of DNA sequences are reviewed and their basic assumptions are verified by statistical analysis of bacterial DNA sequences. On the ground of this analysis, the definition of non-informative genetic sequence is introduced and a mathematical model of “genetic noise” is proposed. Computer simulations of non-coding (non-informative) nucleotide sequence evolution are performed and resulting sequences are compared with native ones. The task of visualisation of genetic sequences is an important part of the work. The main tasks of the work are the following: 1. to analyse the statistical features (independence, Markovity, long-range dependence, etc.) of bacterial DNA sequences, especially non-coding ones, 2. to formulate a definition of a non-informative nucleotide sequence (“genetic noise”) and to propose its mathematical model, 3. using the methodology of functional data analysis and the distance metrics between oligonucleotides, to propose an efficient method for nucleotide sequence visualisation. General Conclusions: 1. The probability model of non-informative nucleotide sequence or, in other words, “genetic noise” (an analogue of the “white noise”) is proposed and its properties are studied mainly by computer simulation. The long-range dependence in DNA sequences has been extensively studied and is considered as an evidence of their complexity and hierarchical structure. The work reveals that the long-range dependence is intrinsic property of a the “genetic noise” generated by a simple evolution model. 2. Common probabilistic models of genetic sequences usually assume either independency of nucleotides or the first order Markovity. The analysis of dependences of bacteria genomes in non-coding nucleotide sequences has been carried out and hypotheses of independence and Markovity in these sequences have been tested. It have been shown that these hypotheses are rejected in a major part of the sequences. 3. A new measure of the distance between nucleotide sequences and the efficient method for visualisation of nucleotide sequences have been proposed. It facilitates visualisation of a long DNA sequence via a compact and smooth picture of all oligonucleotides of length up to 10 in the sequence.