COMPUTATIONAL TOOLS FOR THE DNA TEXT COMPLEXITY ESTIMATES FOR MICROBIAL GENOMES STRUCTURE ANALYSIS

Abstract

One of the fundamental tasks in bioinformatics involves searching for repeats, which are statistically heterogeneous segments within DNA sequences and complete genomes of microorganisms. Theoretical approaches to analyzing the complexity of macromolecule sequences (DNA, RNA, and proteins) were established prior to the availability of complete genomic sequences. These approaches have experienced a resurgence due to the proliferation of mass parallel sequencing technologies and the exponential growth of accessible data. This article explores contemporary computer methods and existing programs designed to assess DNA text complexity as well as construct profiles of properties for analysing the genomic structures of microorganisms. The article offers a comprehensive overview of available online programs designed for detecting and visualising repeats within genetic text. Furthermore, the paper introduces a novel computer-based implementation of a method to evaluate the linguistic complexity of text and its compression using Lempel-Ziv. This approach aims to identify structural features and anomalies within the genomes of microorganisms. The article also provides examples of profiles generated through the analysis of text complexity. Application of these complexity estimates in the analysis of genome sequences, such as those of the SARS-CoV-2 coronavirus and the Mumps Orthorubulavirus, is discussed. Specific areas of low complexity within the genetic text have been successfully identified in this research.